diff --git a/paper/paper.tex b/paper/paper.tex
index 6c8231d1dd09662c81c1080af2e123838f98a372..4184aaa81fdabb28fef826ec3d180b87cbce3286 100644
--- a/paper/paper.tex
+++ b/paper/paper.tex
@@ -1,589 +1,569 @@
-\documentclass{article}
-
-
-% if you need to pass options to natbib, use, e.g.:
-% \PassOptionsToPackage{numbers, compress}{natbib}
-% before loading neurips_2022
-
-
-% ready for submission
-\usepackage{neurips_2022}
-
-
-% to compile a preprint version, e.g., for submission to arXiv, add add the
-% [preprint] option:
-% \usepackage[preprint]{neurips_2022}
-
-
-% to compile a camera-ready version, add the [final] option, e.g.:
-% \usepackage[final]{neurips_2022}
-
-
-% to avoid loading the natbib package, add option nonatbib:
-% \usepackage[nonatbib]{neurips_2022}
-
-
-\usepackage[utf8]{inputenc} % allow utf-8 input
-\usepackage[T1]{fontenc} % use 8-bit T1 fonts
-\usepackage{hyperref} % hyperlinks
-\usepackage{url} % simple URL typesetting
-\usepackage{booktabs} % professional-quality tables
-\usepackage{amsfonts} % blackboard math symbols
-\usepackage{nicefrac} % compact symbols for 1/2, etc.
-\usepackage{microtype} % microtypography
-\usepackage{xcolor} % colors
-
-
-\title{High-Fidelity Counterfactual Explanations through Conformal Prediction}
-
-
-% The \author macro works with any number of authors. There are two commands
-% used to separate the names and addresses of multiple authors: \And and \AND.
-%
-% Using \And between authors leaves it to LaTeX to determine where to break the
-% lines. Using \AND forces a line break at that point. So, if LaTeX puts 3 of 4
-% authors names on the first line, and the last on the second line, try using
-% \AND instead of \And before the third author name.
-
-
-\author{%
- David S.~Hippocampus\thanks{Use footnote for providing further information
- about author (webpage, alternative address)---\emph{not} for acknowledging
- funding agencies.} \\
- Department of Computer Science\\
- Cranberry-Lemon University\\
- Pittsburgh, PA 15213 \\
- \texttt{hippo@cs.cranberry-lemon.edu} \\
- % examples of more authors
- % \And
- % Coauthor \\
- % Affiliation \\
- % Address \\
- % \texttt{email} \\
- % \AND
- % Coauthor \\
- % Affiliation \\
- % Address \\
- % \texttt{email} \\
- % \And
- % Coauthor \\
- % Affiliation \\
- % Address \\
- % \texttt{email} \\
- % \And
- % Coauthor \\
- % Affiliation \\
- % Address \\
- % \texttt{email} \\
-}
-
-
-\begin{document}
-
-
-\maketitle
-
-
-\begin{abstract}
- The abstract paragraph should be indented \nicefrac{1}{2}~inch (3~picas) on
- both the left- and right-hand margins. Use 10~point type, with a vertical
- spacing (leading) of 11~points. The word \textbf{Abstract} must be centered,
- bold, and in point size 12. Two line spaces precede the abstract. The abstract
- must be limited to one paragraph.
-\end{abstract}
-
-
-\section{Submission of papers to NeurIPS 2022}
-
-
-Please read the instructions below carefully and follow them faithfully.
-
-
-\subsection{Style}
-
-
-Papers to be submitted to NeurIPS 2022 must be prepared according to the
-instructions presented here. Papers may only be up to {\bf nine} pages long,
-including figures. Additional pages \emph{containing only acknowledgments and
-references} are allowed. Papers that exceed the page limit will not be
-reviewed, or in any other way considered for presentation at the conference.
-
-
-The margins in 2022 are the same as those in 2007, which allow for $\sim$$15\%$
-more words in the paper compared to earlier years.
-
-
-Authors are required to use the NeurIPS \LaTeX{} style files obtainable at the
-NeurIPS website as indicated below. Please make sure you use the current files
-and not previous versions. Tweaking the style files may be grounds for
-rejection.
-
-
-\subsection{Retrieval of style files}
-
-
-The style files for NeurIPS and other conference information are available on
-the World Wide Web at
-\begin{center}
- \url{http://www.neurips.cc/}
-\end{center}
-The file \verb+neurips_2022.pdf+ contains these instructions and illustrates the
-various formatting requirements your NeurIPS paper must satisfy.
-
-
-The only supported style file for NeurIPS 2022 is \verb+neurips_2022.sty+,
-rewritten for \LaTeXe{}. \textbf{Previous style files for \LaTeX{} 2.09,
- Microsoft Word, and RTF are no longer supported!}
-
-
-The \LaTeX{} style file contains three optional arguments: \verb+final+, which
-creates a camera-ready copy, \verb+preprint+, which creates a preprint for
-submission to, e.g., arXiv, and \verb+nonatbib+, which will not load the
-\verb+natbib+ package for you in case of package clash.
-
-
-\paragraph{Preprint option}
-If you wish to post a preprint of your work online, e.g., on arXiv, using the
-NeurIPS style, please use the \verb+preprint+ option. This will create a
-nonanonymized version of your work with the text ``Preprint. Work in progress.''
-in the footer. This version may be distributed as you see fit. Please \textbf{do
- not} use the \verb+final+ option, which should \textbf{only} be used for
-papers accepted to NeurIPS.
-
-
-At submission time, please omit the \verb+final+ and \verb+preprint+
-options. This will anonymize your submission and add line numbers to aid
-review. Please do \emph{not} refer to these line numbers in your paper as they
-will be removed during generation of camera-ready copies.
-
-
-The file \verb+neurips_2022.tex+ may be used as a ``shell'' for writing your
-paper. All you have to do is replace the author, title, abstract, and text of
-the paper with your own.
-
-
-The formatting instructions contained in these style files are summarized in
-Sections \ref{gen_inst}, \ref{headings}, and \ref{others} below.
-
-
-\section{General formatting instructions}
-\label{gen_inst}
-
-
-The text must be confined within a rectangle 5.5~inches (33~picas) wide and
-9~inches (54~picas) long. The left margin is 1.5~inch (9~picas). Use 10~point
-type with a vertical spacing (leading) of 11~points. Times New Roman is the
-preferred typeface throughout, and will be selected for you by default.
-Paragraphs are separated by \nicefrac{1}{2}~line space (5.5 points), with no
-indentation.
-
-
-The paper title should be 17~point, initial caps/lower case, bold, centered
-between two horizontal rules. The top rule should be 4~points thick and the
-bottom rule should be 1~point thick. Allow \nicefrac{1}{4}~inch space above and
-below the title to rules. All pages should start at 1~inch (6~picas) from the
-top of the page.
-
-
-For the final version, authors' names are set in boldface, and each name is
-centered above the corresponding address. The lead author's name is to be listed
-first (left-most), and the co-authors' names (if different address) are set to
-follow. If there is only one co-author, list both author and co-author side by
-side.
-
-
-Please pay special attention to the instructions in Section \ref{others}
-regarding figures, tables, acknowledgments, and references.
-
-
-\section{Headings: first level}
-\label{headings}
-
-
-All headings should be lower case (except for first word and proper nouns),
-flush left, and bold.
-
-
-First-level headings should be in 12-point type.
-
-
-\subsection{Headings: second level}
-
-
-Second-level headings should be in 10-point type.
-
-
-\subsubsection{Headings: third level}
-
-
-Third-level headings should be in 10-point type.
-
-
-\paragraph{Paragraphs}
-
-
-There is also a \verb+\paragraph+ command available, which sets the heading in
-bold, flush left, and inline with the text, with the heading followed by 1\,em
-of space.
-
-
-\section{Citations, figures, tables, references}
-\label{others}
-
-
-These instructions apply to everyone.
-
-
-\subsection{Citations within the text}
-
-
-The \verb+natbib+ package will be loaded for you by default. Citations may be
-author/year or numeric, as long as you maintain internal consistency. As to the
-format of the references themselves, any style is acceptable as long as it is
-used consistently.
-
-
-The documentation for \verb+natbib+ may be found at
-\begin{center}
- \url{http://mirrors.ctan.org/macros/latex/contrib/natbib/natnotes.pdf}
-\end{center}
-Of note is the command \verb+\citet+, which produces citations appropriate for
-use in inline text. For example,
-\begin{verbatim}
- \citet{hasselmo} investigated\dots
-\end{verbatim}
-produces
-\begin{quote}
- Hasselmo, et al.\ (1995) investigated\dots
-\end{quote}
-
-
-If you wish to load the \verb+natbib+ package with options, you may add the
-following before loading the \verb+neurips_2022+ package:
-\begin{verbatim}
- \PassOptionsToPackage{options}{natbib}
-\end{verbatim}
-
-
-If \verb+natbib+ clashes with another package you load, you can add the optional
-argument \verb+nonatbib+ when loading the style file:
-\begin{verbatim}
- \usepackage[nonatbib]{neurips_2022}
-\end{verbatim}
-
-
-As submission is double blind, refer to your own published work in the third
-person. That is, use ``In the previous work of Jones et al.\ [4],'' not ``In our
-previous work [4].'' If you cite your other papers that are not widely available
-(e.g., a journal paper under review), use anonymous author names in the
-citation, e.g., an author of the form ``A.\ Anonymous.''
-
-
-\subsection{Footnotes}
-
-
-Footnotes should be used sparingly. If you do require a footnote, indicate
-footnotes with a number\footnote{Sample of the first footnote.} in the
-text. Place the footnotes at the bottom of the page on which they appear.
-Precede the footnote with a horizontal rule of 2~inches (12~picas).
-
-
-Note that footnotes are properly typeset \emph{after} punctuation
-marks.\footnote{As in this example.}
-
-
-\subsection{Figures}
-
-
-\begin{figure}
- \centering
- \fbox{\rule[-.5cm]{0cm}{4cm} \rule[-.5cm]{4cm}{0cm}}
- \caption{Sample figure caption.}
-\end{figure}
-
-
-All artwork must be neat, clean, and legible. Lines should be dark enough for
-purposes of reproduction. The figure number and caption always appear after the
-figure. Place one line space before the figure caption and one line space after
-the figure. The figure caption should be lower case (except for first word and
-proper nouns); figures are numbered consecutively.
-
-
-You may use color figures. However, it is best for the figure captions and the
-paper body to be legible if the paper is printed in either black/white or in
-color.
-
-
-\subsection{Tables}
-
-
-All tables must be centered, neat, clean and legible. The table number and
-title always appear before the table. See Table~\ref{sample-table}.
-
-
-Place one line space before the table title, one line space after the
-table title, and one line space after the table. The table title must
-be lower case (except for first word and proper nouns); tables are
-numbered consecutively.
-
-
-Note that publication-quality tables \emph{do not contain vertical rules.} We
-strongly suggest the use of the \verb+booktabs+ package, which allows for
-typesetting high-quality, professional tables:
-\begin{center}
- \url{https://www.ctan.org/pkg/booktabs}
-\end{center}
-This package was used to typeset Table~\ref{sample-table}.
-
-
-\begin{table}
- \caption{Sample table title}
- \label{sample-table}
- \centering
- \begin{tabular}{lll}
- \toprule
- \multicolumn{2}{c}{Part} \\
- \cmidrule(r){1-2}
- Name & Description & Size ($\mu$m) \\
- \midrule
- Dendrite & Input terminal & $\sim$100 \\
- Axon & Output terminal & $\sim$10 \\
- Soma & Cell body & up to $10^6$ \\
- \bottomrule
- \end{tabular}
-\end{table}
-
-
-\section{Final instructions}
-
-
-Do not change any aspects of the formatting parameters in the style files. In
-particular, do not modify the width or length of the rectangle the text should
-fit into, and do not change font sizes (except perhaps in the
-\textbf{References} section; see below). Please note that pages should be
-numbered.
-
-
-\section{Preparing PDF files}
-
-
-Please prepare submission files with paper size ``US Letter,'' and not, for
-example, ``A4.''
-
-
-Fonts were the main cause of problems in the past years. Your PDF file must only
-contain Type 1 or Embedded TrueType fonts. Here are a few instructions to
-achieve this.
-
-
-\begin{itemize}
-
-
-\item You should directly generate PDF files using \verb+pdflatex+.
-
-
-\item You can check which fonts a PDF files uses. In Acrobat Reader, select the
- menu Files$>$Document Properties$>$Fonts and select Show All Fonts. You can
- also use the program \verb+pdffonts+ which comes with \verb+xpdf+ and is
- available out-of-the-box on most Linux machines.
-
-
-\item The IEEE has recommendations for generating PDF files whose fonts are also
- acceptable for NeurIPS. Please see
- \url{http://www.emfield.org/icuwb2010/downloads/IEEE-PDF-SpecV32.pdf}
-
-
-\item \verb+xfig+ "patterned" shapes are implemented with bitmap fonts. Use
- "solid" shapes instead.
-
-
-\item The \verb+\bbold+ package almost always uses bitmap fonts. You should use
- the equivalent AMS Fonts:
-\begin{verbatim}
- \usepackage{amsfonts}
-\end{verbatim}
-followed by, e.g., \verb+\mathbb{R}+, \verb+\mathbb{N}+, or \verb+\mathbb{C}+
-for $\mathbb{R}$, $\mathbb{N}$ or $\mathbb{C}$. You can also use the following
-workaround for reals, natural and complex:
-\begin{verbatim}
- \newcommand{\RR}{I\!\!R} %real numbers
- \newcommand{\Nat}{I\!\!N} %natural numbers
- \newcommand{\CC}{I\!\!\!\!C} %complex numbers
-\end{verbatim}
-Note that \verb+amsfonts+ is automatically loaded by the \verb+amssymb+ package.
-
-
-\end{itemize}
-
-
-If your file contains type 3 fonts or non embedded TrueType fonts, we will ask
-you to fix it.
-
-
-\subsection{Margins in \LaTeX{}}
-
-
-Most of the margin problems come from figures positioned by hand using
-\verb+\special+ or other commands. We suggest using the command
-\verb+\includegraphics+ from the \verb+graphicx+ package. Always specify the
-figure width as a multiple of the line width as in the example below:
-\begin{verbatim}
- \usepackage[pdftex]{graphicx} ...
- \includegraphics[width=0.8\linewidth]{myfile.pdf}
-\end{verbatim}
-See Section 4.4 in the graphics bundle documentation
-(\url{http://mirrors.ctan.org/macros/latex/required/graphics/grfguide.pdf})
-
-
-A number of width problems arise when \LaTeX{} cannot properly hyphenate a
-line. Please give LaTeX hyphenation hints using the \verb+\-+ command when
-necessary.
-
-
-\begin{ack}
-Use unnumbered first level headings for the acknowledgments. All acknowledgments
-go at the end of the paper before the list of references. Moreover, you are required to declare
-funding (financial activities supporting the submitted work) and competing interests (related financial activities outside the submitted work).
-More information about this disclosure can be found at: \url{https://neurips.cc/Conferences/2022/PaperInformation/FundingDisclosure}.
-
-
-Do {\bf not} include this section in the anonymized submission, only in the final paper. You can use the \texttt{ack} environment provided in the style file to autmoatically hide this section in the anonymized submission.
-\end{ack}
-
-
-\section*{References}
-
-
-References follow the acknowledgments. Use unnumbered first-level heading for
-the references. Any choice of citation style is acceptable as long as you are
-consistent. It is permissible to reduce the font size to \verb+small+ (9 point)
-when listing the references.
-Note that the Reference section does not count towards the page limit.
-\medskip
-
-
-{
-\small
-
-
-[1] Alexander, J.A.\ \& Mozer, M.C.\ (1995) Template-based algorithms for
-connectionist rule extraction. In G.\ Tesauro, D.S.\ Touretzky and T.K.\ Leen
-(eds.), {\it Advances in Neural Information Processing Systems 7},
-pp.\ 609--616. Cambridge, MA: MIT Press.
-
-
-[2] Bower, J.M.\ \& Beeman, D.\ (1995) {\it The Book of GENESIS: Exploring
- Realistic Neural Models with the GEneral NEural SImulation System.} New York:
-TELOS/Springer--Verlag.
-
-
-[3] Hasselmo, M.E., Schnell, E.\ \& Barkai, E.\ (1995) Dynamics of learning and
-recall at excitatory recurrent synapses and cholinergic modulation in rat
-hippocampal region CA3. {\it Journal of Neuroscience} {\bf 15}(7):5249-5262.
-}
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\section*{Checklist}
-
-
-%%% BEGIN INSTRUCTIONS %%%
-The checklist follows the references. Please
-read the checklist guidelines carefully for information on how to answer these
-questions. For each question, change the default \answerTODO{} to \answerYes{},
-\answerNo{}, or \answerNA{}. You are strongly encouraged to include a {\bf
-justification to your answer}, either by referencing the appropriate section of
-your paper or providing a brief inline description. For example:
-\begin{itemize}
- \item Did you include the license to the code and datasets? \answerYes{See Section~\ref{gen_inst}.}
- \item Did you include the license to the code and datasets? \answerNo{The code and the data are proprietary.}
- \item Did you include the license to the code and datasets? \answerNA{}
-\end{itemize}
-Please do not modify the questions and only use the provided macros for your
-answers. Note that the Checklist section does not count towards the page
-limit. In your paper, please delete this instructions block and only keep the
-Checklist section heading above along with the questions/answers below.
-%%% END INSTRUCTIONS %%%
-
-
-\begin{enumerate}
-
-
-\item For all authors...
-\begin{enumerate}
- \item Do the main claims made in the abstract and introduction accurately reflect the paper's contributions and scope?
- \answerTODO{}
- \item Did you describe the limitations of your work?
- \answerTODO{}
- \item Did you discuss any potential negative societal impacts of your work?
- \answerTODO{}
- \item Have you read the ethics review guidelines and ensured that your paper conforms to them?
- \answerTODO{}
-\end{enumerate}
-
-
-\item If you are including theoretical results...
-\begin{enumerate}
- \item Did you state the full set of assumptions of all theoretical results?
- \answerTODO{}
- \item Did you include complete proofs of all theoretical results?
- \answerTODO{}
-\end{enumerate}
-
-
-\item If you ran experiments...
-\begin{enumerate}
- \item Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)?
- \answerTODO{}
- \item Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)?
- \answerTODO{}
- \item Did you report error bars (e.g., with respect to the random seed after running experiments multiple times)?
- \answerTODO{}
- \item Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)?
- \answerTODO{}
-\end{enumerate}
-
-
-\item If you are using existing assets (e.g., code, data, models) or curating/releasing new assets...
-\begin{enumerate}
- \item If your work uses existing assets, did you cite the creators?
- \answerTODO{}
- \item Did you mention the license of the assets?
- \answerTODO{}
- \item Did you include any new assets either in the supplemental material or as a URL?
- \answerTODO{}
- \item Did you discuss whether and how consent was obtained from people whose data you're using/curating?
- \answerTODO{}
- \item Did you discuss whether the data you are using/curating contains personally identifiable information or offensive content?
- \answerTODO{}
-\end{enumerate}
-
-
-\item If you used crowdsourcing or conducted research with human subjects...
-\begin{enumerate}
- \item Did you include the full text of instructions given to participants and screenshots, if applicable?
- \answerTODO{}
- \item Did you describe any potential participant risks, with links to Institutional Review Board (IRB) approvals, if applicable?
- \answerTODO{}
- \item Did you include the estimated hourly wage paid to participants and the total amount spent on participant compensation?
- \answerTODO{}
-\end{enumerate}
-
-
-\end{enumerate}
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
-\appendix
-
-
-\section{Appendix}
-
-
-Optionally include extra information (complete proofs, additional experiments and plots) in the appendix.
-This section will often be part of the supplemental material.
-
-
+\documentclass{article}
+
+% if you need to pass options to natbib, use, e.g.:
+% \PassOptionsToPackage{numbers, compress}{natbib}
+% before loading neurips_2022
+
+
+% ready for submission
+\usepackage{neurips_2022}
+
+
+% to compile a preprint version, e.g., for submission to arXiv, add add the
+% [preprint] option:
+% \usepackage[preprint]{neurips_2022}
+
+
+% to compile a camera-ready version, add the [final] option, e.g.:
+% \usepackage[final]{neurips_2022}
+
+
+% to avoid loading the natbib package, add option nonatbib:
+% \usepackage[nonatbib]{neurips_2022}
+
+
+\usepackage[utf8]{inputenc} % allow utf-8 input
+\usepackage[T1]{fontenc} % use 8-bit T1 fonts
+\usepackage{hyperref} % hyperlinks
+\usepackage{url} % simple URL typesetting
+\usepackage{booktabs} % professional-quality tables
+\usepackage{amsfonts} % blackboard math symbols
+\usepackage{nicefrac} % compact symbols for 1/2, etc.
+\usepackage{microtype} % microtypography
+\usepackage{xcolor} % colors
+
+
+\title{High-Fidelity Counterfactual Explanations through Conformal Prediction}
+
+
+% The \author macro works with any number of authors. There are two commands
+% used to separate the names and addresses of multiple authors: \And and \AND.
+%
+% Using \And between authors leaves it to LaTeX to determine where to break the
+% lines. Using \AND forces a line break at that point. So, if LaTeX puts 3 of 4
+% authors names on the first line, and the last on the second line, try using
+% \AND instead of \And before the third author name.
+
+
+\author{%
+ David S.~Hippocampus\thanks{Use footnote for providing further information
+ about author (webpage, alternative address)---\emph{not} for acknowledging
+ funding agencies.} \\
+ Department of Computer Science\\
+ Cranberry-Lemon University\\
+ Pittsburgh, PA 15213 \\
+ \texttt{hippo@cs.cranberry-lemon.edu} \\
+ % examples of more authors
+ % \And
+ % Coauthor \\
+ % Affiliation \\
+ % Address \\
+ % \texttt{email} \\
+ % \AND
+ % Coauthor \\
+ % Affiliation \\
+ % Address \\
+ % \texttt{email} \\
+ % \And
+ % Coauthor \\
+ % Affiliation \\
+ % Address \\
+ % \texttt{email} \\
+ % \And
+ % Coauthor \\
+ % Affiliation \\
+ % Address \\
+ % \texttt{email} \\
+}
+
+
+\begin{document}
+
+\maketitle
+
+
+\begin{abstract}
+ The abstract paragraph should be indented \nicefrac{1}{2}~inch (3~picas) on
+ both the left- and right-hand margins. Use 10~point type, with a vertical
+ spacing (leading) of 11~points. The word \textbf{Abstract} must be centered,
+ bold, and in point size 12. Two line spaces precede the abstract. The abstract
+ must be limited to one paragraph.
+\end{abstract}
+
+
+\section{Submission of papers to NeurIPS 2022}
+
+
+Please read the instructions below carefully and follow them faithfully.
+
+
+\subsection{Style}
+
+
+Papers to be submitted to NeurIPS 2022 must be prepared according to the
+instructions presented here. Papers may only be up to {\bf nine} pages long,
+including figures. Additional pages \emph{containing only acknowledgments and
+references} are allowed. Papers that exceed the page limit will not be
+reviewed, or in any other way considered for presentation at the conference.
+
+
+The margins in 2022 are the same as those in 2007, which allow for $\sim$$15\%$
+more words in the paper compared to earlier years.
+
+\cite{abadie2002instrumental}
+
+Authors are required to use the NeurIPS \LaTeX{} style files obtainable at the
+NeurIPS website as indicated below. Please make sure you use the current files
+and not previous versions. Tweaking the style files may be grounds for
+rejection.
+
+
+\subsection{Retrieval of style files}
+
+
+The style files for NeurIPS and other conference information are available on
+the World Wide Web at
+\begin{center}
+ \url{http://www.neurips.cc/}
+\end{center}
+The file \verb+neurips_2022.pdf+ contains these instructions and illustrates the
+various formatting requirements your NeurIPS paper must satisfy.
+
+
+The only supported style file for NeurIPS 2022 is \verb+neurips_2022.sty+,
+rewritten for \LaTeXe{}. \textbf{Previous style files for \LaTeX{} 2.09,
+ Microsoft Word, and RTF are no longer supported!}
+
+
+The \LaTeX{} style file contains three optional arguments: \verb+final+, which
+creates a camera-ready copy, \verb+preprint+, which creates a preprint for
+submission to, e.g., arXiv, and \verb+nonatbib+, which will not load the
+\verb+natbib+ package for you in case of package clash.
+
+
+\paragraph{Preprint option}
+If you wish to post a preprint of your work online, e.g., on arXiv, using the
+NeurIPS style, please use the \verb+preprint+ option. This will create a
+nonanonymized version of your work with the text ``Preprint. Work in progress.''
+in the footer. This version may be distributed as you see fit. Please \textbf{do
+ not} use the \verb+final+ option, which should \textbf{only} be used for
+papers accepted to NeurIPS.
+
+
+At submission time, please omit the \verb+final+ and \verb+preprint+
+options. This will anonymize your submission and add line numbers to aid
+review. Please do \emph{not} refer to these line numbers in your paper as they
+will be removed during generation of camera-ready copies.
+
+
+The file \verb+neurips_2022.tex+ may be used as a ``shell'' for writing your
+paper. All you have to do is replace the author, title, abstract, and text of
+the paper with your own.
+
+
+The formatting instructions contained in these style files are summarized in
+Sections \ref{gen_inst}, \ref{headings}, and \ref{others} below.
+
+
+\section{General formatting instructions}
+\label{gen_inst}
+
+
+The text must be confined within a rectangle 5.5~inches (33~picas) wide and
+9~inches (54~picas) long. The left margin is 1.5~inch (9~picas). Use 10~point
+type with a vertical spacing (leading) of 11~points. Times New Roman is the
+preferred typeface throughout, and will be selected for you by default.
+Paragraphs are separated by \nicefrac{1}{2}~line space (5.5 points), with no
+indentation.
+
+
+The paper title should be 17~point, initial caps/lower case, bold, centered
+between two horizontal rules. The top rule should be 4~points thick and the
+bottom rule should be 1~point thick. Allow \nicefrac{1}{4}~inch space above and
+below the title to rules. All pages should start at 1~inch (6~picas) from the
+top of the page.
+
+
+For the final version, authors' names are set in boldface, and each name is
+centered above the corresponding address. The lead author's name is to be listed
+first (left-most), and the co-authors' names (if different address) are set to
+follow. If there is only one co-author, list both author and co-author side by
+side.
+
+
+Please pay special attention to the instructions in Section \ref{others}
+regarding figures, tables, acknowledgments, and references.
+
+
+\section{Headings: first level}
+\label{headings}
+
+
+All headings should be lower case (except for first word and proper nouns),
+flush left, and bold.
+
+
+First-level headings should be in 12-point type.
+
+
+\subsection{Headings: second level}
+
+
+Second-level headings should be in 10-point type.
+
+
+\subsubsection{Headings: third level}
+
+
+Third-level headings should be in 10-point type.
+
+
+\paragraph{Paragraphs}
+
+
+There is also a \verb+\paragraph+ command available, which sets the heading in
+bold, flush left, and inline with the text, with the heading followed by 1\,em
+of space.
+
+
+\section{Citations, figures, tables, references}
+\label{others}
+
+
+These instructions apply to everyone.
+
+
+\subsection{Citations within the text}
+
+
+The \verb+natbib+ package will be loaded for you by default. Citations may be
+author/year or numeric, as long as you maintain internal consistency. As to the
+format of the references themselves, any style is acceptable as long as it is
+used consistently.
+
+
+The documentation for \verb+natbib+ may be found at
+\begin{center}
+ \url{http://mirrors.ctan.org/macros/latex/contrib/natbib/natnotes.pdf}
+\end{center}
+Of note is the command \verb+\citet+, which produces citations appropriate for
+use in inline text. For example,
+\begin{verbatim}
+ \citet{hasselmo} investigated\dots
+\end{verbatim}
+produces
+\begin{quote}
+ Hasselmo, et al.\ (1995) investigated\dots
+\end{quote}
+
+
+If you wish to load the \verb+natbib+ package with options, you may add the
+following before loading the \verb+neurips_2022+ package:
+\begin{verbatim}
+ \PassOptionsToPackage{options}{natbib}
+\end{verbatim}
+
+
+If \verb+natbib+ clashes with another package you load, you can add the optional
+argument \verb+nonatbib+ when loading the style file:
+\begin{verbatim}
+ \usepackage[nonatbib]{neurips_2022}
+\end{verbatim}
+
+
+As submission is double blind, refer to your own published work in the third
+person. That is, use ``In the previous work of Jones et al.\ [4],'' not ``In our
+previous work [4].'' If you cite your other papers that are not widely available
+(e.g., a journal paper under review), use anonymous author names in the
+citation, e.g., an author of the form ``A.\ Anonymous.''
+
+
+\subsection{Footnotes}
+
+
+Footnotes should be used sparingly. If you do require a footnote, indicate
+footnotes with a number\footnote{Sample of the first footnote.} in the
+text. Place the footnotes at the bottom of the page on which they appear.
+Precede the footnote with a horizontal rule of 2~inches (12~picas).
+
+
+Note that footnotes are properly typeset \emph{after} punctuation
+marks.\footnote{As in this example.}
+
+
+\subsection{Figures}
+
+
+\begin{figure}
+ \centering
+ \fbox{\rule[-.5cm]{0cm}{4cm} \rule[-.5cm]{4cm}{0cm}}
+ \caption{Sample figure caption.}
+\end{figure}
+
+
+All artwork must be neat, clean, and legible. Lines should be dark enough for
+purposes of reproduction. The figure number and caption always appear after the
+figure. Place one line space before the figure caption and one line space after
+the figure. The figure caption should be lower case (except for first word and
+proper nouns); figures are numbered consecutively.
+
+
+You may use color figures. However, it is best for the figure captions and the
+paper body to be legible if the paper is printed in either black/white or in
+color.
+
+
+\subsection{Tables}
+
+
+All tables must be centered, neat, clean and legible. The table number and
+title always appear before the table. See Table~\ref{sample-table}.
+
+
+Place one line space before the table title, one line space after the
+table title, and one line space after the table. The table title must
+be lower case (except for first word and proper nouns); tables are
+numbered consecutively.
+
+
+Note that publication-quality tables \emph{do not contain vertical rules.} We
+strongly suggest the use of the \verb+booktabs+ package, which allows for
+typesetting high-quality, professional tables:
+\begin{center}
+ \url{https://www.ctan.org/pkg/booktabs}
+\end{center}
+This package was used to typeset Table~\ref{sample-table}.
+
+
+\begin{table}
+ \caption{Sample table title}
+ \label{sample-table}
+ \centering
+ \begin{tabular}{lll}
+ \toprule
+ \multicolumn{2}{c}{Part} \\
+ \cmidrule(r){1-2}
+ Name & Description & Size ($\mu$m) \\
+ \midrule
+ Dendrite & Input terminal & $\sim$100 \\
+ Axon & Output terminal & $\sim$10 \\
+ Soma & Cell body & up to $10^6$ \\
+ \bottomrule
+ \end{tabular}
+\end{table}
+
+
+\section{Final instructions}
+
+
+Do not change any aspects of the formatting parameters in the style files. In
+particular, do not modify the width or length of the rectangle the text should
+fit into, and do not change font sizes (except perhaps in the
+\textbf{References} section; see below). Please note that pages should be
+numbered.
+
+
+\section{Preparing PDF files}
+
+
+Please prepare submission files with paper size ``US Letter,'' and not, for
+example, ``A4.''
+
+
+Fonts were the main cause of problems in the past years. Your PDF file must only
+contain Type 1 or Embedded TrueType fonts. Here are a few instructions to
+achieve this.
+
+
+\begin{itemize}
+
+
+\item You should directly generate PDF files using \verb+pdflatex+.
+
+
+\item You can check which fonts a PDF files uses. In Acrobat Reader, select the
+ menu Files$>$Document Properties$>$Fonts and select Show All Fonts. You can
+ also use the program \verb+pdffonts+ which comes with \verb+xpdf+ and is
+ available out-of-the-box on most Linux machines.
+
+
+\item The IEEE has recommendations for generating PDF files whose fonts are also
+ acceptable for NeurIPS. Please see
+ \url{http://www.emfield.org/icuwb2010/downloads/IEEE-PDF-SpecV32.pdf}
+
+
+\item \verb+xfig+ "patterned" shapes are implemented with bitmap fonts. Use
+ "solid" shapes instead.
+
+
+\item The \verb+\bbold+ package almost always uses bitmap fonts. You should use
+ the equivalent AMS Fonts:
+\begin{verbatim}
+ \usepackage{amsfonts}
+\end{verbatim}
+followed by, e.g., \verb+\mathbb{R}+, \verb+\mathbb{N}+, or \verb+\mathbb{C}+
+for $\mathbb{R}$, $\mathbb{N}$ or $\mathbb{C}$. You can also use the following
+workaround for reals, natural and complex:
+\begin{verbatim}
+ \newcommand{\RR}{I\!\!R} %real numbers
+ \newcommand{\Nat}{I\!\!N} %natural numbers
+ \newcommand{\CC}{I\!\!\!\!C} %complex numbers
+\end{verbatim}
+Note that \verb+amsfonts+ is automatically loaded by the \verb+amssymb+ package.
+
+
+\end{itemize}
+
+
+If your file contains type 3 fonts or non embedded TrueType fonts, we will ask
+you to fix it.
+
+
+\subsection{Margins in \LaTeX{}}
+
+
+Most of the margin problems come from figures positioned by hand using
+\verb+\special+ or other commands. We suggest using the command
+\verb+\includegraphics+ from the \verb+graphicx+ package. Always specify the
+figure width as a multiple of the line width as in the example below:
+\begin{verbatim}
+ \usepackage[pdftex]{graphicx} ...
+ \includegraphics[width=0.8\linewidth]{myfile.pdf}
+\end{verbatim}
+See Section 4.4 in the graphics bundle documentation
+(\url{http://mirrors.ctan.org/macros/latex/required/graphics/grfguide.pdf})
+
+
+A number of width problems arise when \LaTeX{} cannot properly hyphenate a
+line. Please give LaTeX hyphenation hints using the \verb+\-+ command when
+necessary.
+
+
+\begin{ack}
+Use unnumbered first level headings for the acknowledgments. All acknowledgments
+go at the end of the paper before the list of references. Moreover, you are required to declare
+funding (financial activities supporting the submitted work) and competing interests (related financial activities outside the submitted work).
+More information about this disclosure can be found at: \url{https://neurips.cc/Conferences/2022/PaperInformation/FundingDisclosure}.
+
+
+Do {\bf not} include this section in the anonymized submission, only in the final paper. You can use the \texttt{ack} environment provided in the style file to autmoatically hide this section in the anonymized submission.
+\end{ack}
+
+
+\section*{References}
+
+
+References follow the acknowledgments. Use unnumbered first-level heading for
+the references. Any choice of citation style is acceptable as long as you are
+consistent. It is permissible to reduce the font size to \verb+small+ (9 point)
+when listing the references.
+Note that the Reference section does not count towards the page limit.
+
+\medskip
+
+\bibliography{paper/references}
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\section*{Checklist}
+
+
+%%% BEGIN INSTRUCTIONS %%%
+The checklist follows the references. Please
+read the checklist guidelines carefully for information on how to answer these
+questions. For each question, change the default \answerTODO{} to \answerYes{},
+\answerNo{}, or \answerNA{}. You are strongly encouraged to include a {\bf
+justification to your answer}, either by referencing the appropriate section of
+your paper or providing a brief inline description. For example:
+\begin{itemize}
+ \item Did you include the license to the code and datasets? \answerYes{See Section~\ref{gen_inst}.}
+ \item Did you include the license to the code and datasets? \answerNo{The code and the data are proprietary.}
+ \item Did you include the license to the code and datasets? \answerNA{}
+\end{itemize}
+Please do not modify the questions and only use the provided macros for your
+answers. Note that the Checklist section does not count towards the page
+limit. In your paper, please delete this instructions block and only keep the
+Checklist section heading above along with the questions/answers below.
+%%% END INSTRUCTIONS %%%
+
+
+\begin{enumerate}
+
+
+\item For all authors...
+\begin{enumerate}
+ \item Do the main claims made in the abstract and introduction accurately reflect the paper's contributions and scope?
+ \answerTODO{}
+ \item Did you describe the limitations of your work?
+ \answerTODO{}
+ \item Did you discuss any potential negative societal impacts of your work?
+ \answerTODO{}
+ \item Have you read the ethics review guidelines and ensured that your paper conforms to them?
+ \answerTODO{}
+\end{enumerate}
+
+
+\item If you are including theoretical results...
+\begin{enumerate}
+ \item Did you state the full set of assumptions of all theoretical results?
+ \answerTODO{}
+ \item Did you include complete proofs of all theoretical results?
+ \answerTODO{}
+\end{enumerate}
+
+
+\item If you ran experiments...
+\begin{enumerate}
+ \item Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)?
+ \answerTODO{}
+ \item Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)?
+ \answerTODO{}
+ \item Did you report error bars (e.g., with respect to the random seed after running experiments multiple times)?
+ \answerTODO{}
+ \item Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)?
+ \answerTODO{}
+\end{enumerate}
+
+
+\item If you are using existing assets (e.g., code, data, models) or curating/releasing new assets...
+\begin{enumerate}
+ \item If your work uses existing assets, did you cite the creators?
+ \answerTODO{}
+ \item Did you mention the license of the assets?
+ \answerTODO{}
+ \item Did you include any new assets either in the supplemental material or as a URL?
+ \answerTODO{}
+ \item Did you discuss whether and how consent was obtained from people whose data you're using/curating?
+ \answerTODO{}
+ \item Did you discuss whether the data you are using/curating contains personally identifiable information or offensive content?
+ \answerTODO{}
+\end{enumerate}
+
+
+\item If you used crowdsourcing or conducted research with human subjects...
+\begin{enumerate}
+ \item Did you include the full text of instructions given to participants and screenshots, if applicable?
+ \answerTODO{}
+ \item Did you describe any potential participant risks, with links to Institutional Review Board (IRB) approvals, if applicable?
+ \answerTODO{}
+ \item Did you include the estimated hourly wage paid to participants and the total amount spent on participant compensation?
+ \answerTODO{}
+\end{enumerate}
+
+
+\end{enumerate}
+
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+
+\appendix
+
+
+\section{Appendix}
+
+
+Optionally include extra information (complete proofs, additional experiments and plots) in the appendix.
+This section will often be part of the supplemental material.
+
+
\end{document}
\ No newline at end of file
diff --git a/paper/references.bib b/paper/references.bib
new file mode 100644
index 0000000000000000000000000000000000000000..dbd5fd69d0a1a0fb8fe28a43f98e3a5b492f6877
--- /dev/null
+++ b/paper/references.bib
@@ -0,0 +1,1666 @@
+@inproceedings{LakkarajuExplanations,
+ title = {{" How Do I Fool You?" Manipulating User Trust via Misleading Black Box Explanations}},
+ booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
+ author = {Lakkaraju, Himabindu and Bastani, Osbert},
+ pages = {79--85}
+}
+
+@inproceedings{RibeiroWhyClassifier,
+ title = {{"Why Should i Trust You?" Explaining the Predictions of Any Classifier}},
+ booktitle = {Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
+ author = {Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
+ pages = {1135--1144}
+}
+
+@inproceedings{HannekeALearning,
+ title = {{A Bound on the Label Complexity of Agnostic Active Learning}},
+ booktitle = {Proceedings of the 24th International Conference on Machine Learning},
+ author = {Hanneke, Steve},
+ pages = {353--360}
+}
+
+@article{deOliveiraAData,
+ title = {{A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data}},
+ author = {de Oliveira, Raphael Mazzine Barbosa and Martens, David},
+ number = {16},
+ pages = {7274},
+ volume = {11}
+}
+
+@unpublished{AngelopoulosAQuantification,
+ title = {{A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification}},
+ author = {Angelopoulos, Anastasios N and Bates, Stephen},
+ arxivId = {2107.07511}
+}
+
+@article{GrettonATest,
+ title = {{A Kernel Two-Sample Test}},
+ author = {Gretton, Arthur and Borgwardt, Karsten M and Rasch, Malte J and Sch{\"{o}}lkopf, Bernhard and Smola, Alexander},
+ number = {1},
+ pages = {723--773},
+ volume = {13}
+}
+
+@article{McCullochAActivity,
+ title = {{A Logical Calculus of the Ideas Immanent in Nervous Activity}},
+ author = {McCulloch, Warren S and Pitts, Walter},
+ number = {1},
+ pages = {99--115},
+ volume = {52}
+}
+
+@article{JolliffeALASSO,
+ title = {{A Modified Principal Component Technique Based on the LASSO}},
+ author = {Jolliffe, Ian T and Trendafilov, Nickolay T and Uddin, Mudassir},
+ number = {3},
+ pages = {531--547},
+ volume = {12}
+}
+
+@book{FriedmanA1867-1960,
+ title = {{A Monetary History of the United States, 1867-1960}},
+ author = {Friedman, Milton and Schwartz, Anna Jacobson},
+ volume = {14},
+ publisher = {Princeton University Press}
+}
+
+@article{WittenAAnalysis,
+ title = {{A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis}},
+ author = {Witten, Daniela M and Tibshirani, Robert and Hastie, Trevor},
+ number = {3},
+ pages = {515--534},
+ volume = {10}
+}
+
+@article{SturmAHorse,
+ title = {{A Simple Method to Determine If a Music Information Retrieval System Is a ``Horse''}},
+ author = {Sturm, Bob L},
+ number = {6},
+ pages = {1636--1644},
+ volume = {16}
+}
+
+@article{HsiehASelectivity,
+ title = {{A Social Interactions Model with Endogenous Friendship Formation and Selectivity}},
+ author = {Hsieh, Chih-Sheng and Lee, Lung Fei},
+ number = {2},
+ pages = {301--319},
+ volume = {31}
+}
+
+@unpublished{KarimiAProspects,
+ title = {{A Survey of Algorithmic Recourse: Definitions, Formulations, Solutions, and Prospects}},
+ author = {Karimi, Amir-Hossein and Barthe, Gilles and Sch{\"{o}}lkopf, Bernhard and Valera, Isabel},
+ arxivId = {2010.04050}
+}
+
+@unpublished{BrancoADistributions,
+ title = {{A Survey of Predictive Modelling under Imbalanced Distributions}},
+ author = {Branco, Paula and Torgo, Luis and Ribeiro, Rita},
+ arxivId = {1505.01658}
+}
+
+@article{GamaAAdaptation,
+ title = {{A Survey on Concept Drift Adaptation}},
+ author = {Gama, João and {\v{Z}}liobait{\.{e}}, Indrė and Bifet, Albert and Pechenizkiy, Mykola and Bouchachia, Abdelhamid},
+ number = {4},
+ pages = {1--37},
+ volume = {46}
+}
+
+@inproceedings{LundbergAPredictions,
+ title = {{A Unified Approach to Interpreting Model Predictions}},
+ booktitle = {Proceedings of the 31st International Conference on Neural Information Processing Systems},
+ author = {Lundberg, Scott M and Lee, Su-In},
+ pages = {4768--4777}
+}
+
+@inproceedings{UstunActionableClassification,
+ title = {{Actionable Recourse in Linear Classification}},
+ booktitle = {Proceedings of the Conference on Fairness, Accountability, and Transparency},
+ author = {Ustun, Berk and Spangher, Alexander and Liu, Yang},
+ pages = {10--19}
+}
+
+@unpublished{KingmaAdam:Optimization,
+ title = {{Adam: A Method for Stochastic Optimization}},
+ author = {Kingma, Diederik P and Ba, Jimmy},
+ arxivId = {1412.6980}
+}
+
+@article{ChettyAdjustmentRecords,
+ title = {{Adjustment Costs, Firm Responses, and Micro vs. Macro Labor Supply Elasticities: Evidence from Danish Tax Records}},
+ author = {Chetty, Raj and Friedman, John N and Olsen, Tore and Pistaferri, Luigi},
+ number = {2},
+ pages = {749--804},
+ volume = {126}
+}
+
+@unpublished{RaghunathanAdversarialGeneralization,
+ title = {{Adversarial Training Can Hurt Generalization}},
+ author = {Raghunathan, Aditi and Xie, Sang Michael and Yang, Fanny and Duchi, John C and Liang, Percy},
+ arxivId = {1906.06032}
+}
+
+@unpublished{KarimiAlgorithmicApproach,
+ title = {{Algorithmic Recourse under Imperfect Causal Knowledge: A Probabilistic Approach}},
+ author = {Karimi, Amir-Hossein and Von K{\"{u}}gelgen, Julius and Sch{\"{o}}lkopf, Bernhard and Valera, Isabel},
+ arxivId = {2006.06831}
+}
+
+@inproceedings{KarimiAlgorithmicInterventions,
+ title = {{Algorithmic Recourse: From Counterfactual Explanations to Interventions}},
+ booktitle = {Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency},
+ author = {Karimi, Amir-Hossein and Sch{\"{o}}lkopf, Bernhard and Valera, Isabel},
+ pages = {353--362}
+}
+
+@book{WassermanAllStatistics,
+ title = {{All of Nonparametric Statistics}},
+ author = {Wasserman, Larry},
+ publisher = {Springer Science {\&} Business Media}
+}
+
+@book{WassermanAllInference,
+ title = {{All of Statistics: A Concise Course in Statistical Inference}},
+ author = {Wasserman, Larry},
+ publisher = {Springer Science {\&} Business Media}
+}
+
+@article{HeckmanAlternativeOverview,
+ title = {{Alternative Methods for Evaluating the Impact of Interventions: An Overview}},
+ author = {Heckman, James J and Robb Jr, Richard},
+ number = {1-2},
+ pages = {239--267},
+ volume = {30}
+}
+
+@article{GrahamAnHeterogeneity,
+ title = {{An Econometric Model of Network Formation with Degree Heterogeneity}},
+ author = {Graham, Bryan S},
+ number = {4},
+ pages = {1033--1063},
+ volume = {85}
+}
+
+@article{ChapelleAnSampling,
+ title = {{An Empirical Evaluation of Thompson Sampling}},
+ author = {Chapelle, Olivier and Li, Lihong},
+ pages = {2249--2257},
+ volume = {24}
+}
+
+@article{MostellerAnUtility,
+ title = {{An Experimental Measurement of Utility}},
+ author = {Mosteller, Frederick and Nogee, Philip},
+ number = {5},
+ pages = {371--404},
+ volume = {59}
+}
+
+@article{FixAnEstimation,
+ title = {{An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation}},
+ author = {Fix, E and Hodges, J},
+ number = {57},
+ pages = {233--238},
+ volume = {3}
+}
+
+@article{ChandolaAnomalySurvey,
+ title = {{Anomaly Detection: A Survey}},
+ author = {Chandola, Varun and Banerjee, Arindam and Kumar, Vipin},
+ number = {3},
+ pages = {1--58},
+ volume = {41}
+}
+
+@article{SimsAreAnalysis,
+ title = {{Are Forecasting Models Usable for Policy Analysis?}},
+ author = {Sims, Christopher A and {others}},
+ number = {Win},
+ pages = {2--16},
+ volume = {10}
+}
+
+@article{DanielssonArtificialRisk,
+ title = {{Artificial Intelligence and Systemic Risk}},
+ author = {Danielsson, Jon and Macrae, Robert and Uthemann, Andreas},
+ pages = {106290}
+}
+
+@misc{OECDArtificialMakers,
+ title = {{Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges and Implications for Policy Makers}},
+ author = {{OECD}},
+ url = {https://www.oecd.org/finance/financial-markets/Artificial-intelligence-machine-learning-big-data-in-finance.pdf}
+}
+
+@misc{OECDArtificialMakersb,
+ title = {{Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges and Implications for Policy Makers}},
+ author = {{OECD}},
+ publisher = {OECD},
+ url = {https://www.oecd.org/finance/financial-markets/Artificial-intelligence-machine-learning-big-data-in-finance.pdf}
+}
+
+@misc{ManokhinAwesomePrediction,
+ title = {{Awesome Conformal Prediction}},
+ author = {Manokhin, Valery}
+}
+
+@article{KirschBatchbald:Learning,
+ title = {{Batchbald: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning}},
+ author = {Kirsch, Andreas and Van Amersfoort, Joost and Gal, Yarin},
+ pages = {7026--7037},
+ volume = {32}
+}
+
+@unpublished{HoffBayes-OptimalControl,
+ title = {{Bayes-Optimal Prediction with Frequentist Coverage Control}},
+ author = {Hoff, Peter},
+ arxivId = {2105.14045}
+}
+
+@unpublished{HoulsbyBayesianLearning,
+ title = {{Bayesian Active Learning for Classification and Preference Learning}},
+ author = {Houlsby, Neil and Husz{\'{a}}r, Ferenc and Ghahramani, Zoubin and Lengyel, Máté},
+ arxivId = {1112.5745}
+}
+
+@book{GelmanBayesianAnalysis,
+ title = {{Bayesian Data Analysis}},
+ author = {Gelman, Andrew and Carlin, John B and Stern, Hal S and Dunson, David B and Vehtari, Aki and Rubin, Donald B},
+ publisher = {CRC press}
+}
+
+@incollection{GoanBayesianSurvey,
+ title = {{Bayesian Neural Networks: An Introduction and Survey}},
+ booktitle = {Case Studies in Applied Bayesian Data Science},
+ author = {Goan, Ethan and Fookes, Clinton},
+ pages = {45--87},
+ publisher = {Springer}
+}
+
+@unpublished{StantonBayesianGuarantees,
+ title = {{Bayesian Optimization with Conformal Coverage Guarantees}},
+ author = {Stanton, Samuel and Maddox, Wesley and Wilson, Andrew Gordon},
+ arxivId = {2210.12496}
+}
+
+@article{LeeBestDisturbances,
+ title = {{Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances}},
+ author = {Lee, Lung-fei},
+ number = {4},
+ pages = {307--335},
+ volume = {22}
+}
+
+@unpublished{Navarro-MartinezBridgingDonations,
+ title = {{Bridging the Gap between the Lab and the Field: Dictator Games and Donations}},
+ author = {Navarro-Martinez, Daniel and Wang, Xinghua}
+}
+
+@unpublished{PawelczykCarla:Algorithms,
+ title = {{Carla: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms}},
+ author = {Pawelczyk, Martin and Bielawski, Sascha and van den Heuvel, Johannes and Richter, Tobias and Kasneci, Gjergji},
+ arxivId = {2108.00783}
+}
+
+@article{DehejiaCausalPrograms,
+ title = {{Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs}},
+ author = {Dehejia, Rajeev H and Wahba, Sadek},
+ number = {448},
+ pages = {1053--1062},
+ volume = {94}
+}
+
+@article{SimonsonChoiceEffects,
+ title = {{Choice Based on Reasons: The Case of Attraction and Compromise Effects}},
+ author = {Simonson, Itamar},
+ number = {2},
+ pages = {158--174},
+ volume = {16}
+}
+
+@article{FalkCleanEffects,
+ title = {{Clean Evidence on Peer Effects}},
+ author = {Falk, Armin and Ichino, Andrea},
+ number = {1},
+ pages = {39--57},
+ volume = {24}
+}
+
+@article{FehrCooperationExperiments,
+ title = {{Cooperation and Punishment in Public Goods Experiments}},
+ author = {Fehr, Ernst and Gachter, Simon},
+ number = {4},
+ pages = {980--994},
+ volume = {90}
+}
+
+@article{SlackCounterfactualManipulated,
+ title = {{Counterfactual Explanations Can Be Manipulated}},
+ author = {Slack, Dylan and Hilgard, Anna and Lakkaraju, Himabindu and Singh, Sameer},
+ volume = {34}
+}
+
+@unpublished{SpoonerCounterfactualModels,
+ title = {{Counterfactual Explanations for Arbitrary Regression Models}},
+ author = {Spooner, Thomas and Dervovic, Danial and Long, Jason and Shepard, Jon and Chen, Jiahao and Magazzeni, Daniele},
+ arxivId = {2106.15212}
+}
+
+@unpublished{VermaCounterfactualReview,
+ title = {{Counterfactual Explanations for Machine Learning: A Review}},
+ author = {Verma, Sahil and Dickerson, John and Hines, Keegan},
+ arxivId = {2010.10596}
+}
+
+@inproceedings{DaiCounterfactualXai,
+ title = {{Counterfactual Explanations for Prediction and Diagnosis in Xai}},
+ author = {Dai, Xinyue and Keane, Mark T and Shalloo, Laurence and Ruelle, Elodie and Byrne, Ruth M J},
+ pages = {215--226}
+}
+
+@article{WachterCounterfactualGDPR,
+ title = {{Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR}},
+ author = {Wachter, Sandra and Mittelstadt, Brent and Russell, Chris},
+ pages = {841},
+ volume = {31}
+}
+
+@misc{AltmeyerCounterfactualExplanations.JlRecourse,
+ title = {{CounterfactualExplanations.Jl - a Julia Package for Counterfactual Explanations and Algorithmic Recourse}},
+ author = {Altmeyer, Patrick},
+ url = {https://github.com/pat-alt/CounterfactualExplanations.jl}
+}
+
+@misc{AltmeyerCounterfactualExplanations.JlRecourseb,
+ title = {{CounterfactualExplanations.Jl - a Julia Package for Counterfactual Explanations and Algorithmic Recourse}},
+ author = {Altmeyer, Patrick},
+ url = {https://github.com/pat-alt/CounterfactualExplanations.jl}
+}
+
+@book{MorganCounterfactualsInference,
+ title = {{Counterfactuals and Causal Inference}},
+ author = {Morgan, Stephen L and Winship, Christopher},
+ publisher = {Cambridge University Press}
+}
+
+@unpublished{ZhengDagsLearning,
+ title = {{Dags with No Tears: Continuous Optimization for Structure Learning}},
+ author = {Zheng, Xun and Aragam, Bryon and Ravikumar, Pradeep and Xing, Eric P},
+ arxivId = {1803.01422}
+}
+
+@article{BecharaDecidingStrategy,
+ title = {{Deciding Advantageously before Knowing the Advantageous Strategy}},
+ author = {Bechara, Antoine and Damasio, Hanna and Tranel, Daniel and Damasio, Antonio R},
+ number = {5304},
+ pages = {1293--1295},
+ volume = {275}
+}
+
+@inproceedings{GalDeepData,
+ title = {{Deep Bayesian Active Learning with Image Data}},
+ booktitle = {International Conference on Machine Learning},
+ author = {Gal, Yarin and Islam, Riashat and Ghahramani, Zoubin},
+ pages = {1183--1192},
+ publisher = {PMLR}
+}
+
+@book{GoodfellowDeepLearning,
+ title = {{Deep Learning}},
+ author = {Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
+ publisher = {MIT Press}
+}
+
+@unpublished{BorisovDeepSurvey,
+ title = {{Deep Neural Networks and Tabular Data: A Survey}},
+ author = {Borisov, Vadim and Leemann, Tobias and Se{\ss}ler, Kathrin and Haug, Johannes and Pawelczyk, Martin and Kasneci, Gjergji},
+ arxivId = {2110.01889}
+}
+
+@article{AltmeyerDeepData,
+ title = {{Deep Vector Autoregression for Macroeconomic Data}},
+ author = {Altmeyer, Patrick and Agusti, Marc and Vidal-Quadras Costa, Ignacio},
+ url = {https://thevoice.bse.eu/wp-content/uploads/2021/07/ds21-project-agusti-et-al.pdf}
+}
+
+@book{AltmeyerDeepvars:Autoregession,
+ title = {{Deepvars: Deep Vector Autoregession}},
+ author = {Altmeyer, Patrick}
+}
+
+@article{KehoeDefenceMachines,
+ title = {{Defence against Adversarial Attacks Using Classical and Quantum-Enhanced Boltzmann Machines}},
+ author = {Kehoe, Aidan and Wittek, Peter and Xue, Yanbo and Pozas-Kerstjens, Alejandro}
+}
+
+@misc{GroupDetailedOutbreak,
+ title = {{Detailed Epidemiological Data from the COVID-19 Outbreak}},
+ author = {Group, Open COVID-19 Data Working}
+}
+
+@inproceedings{DombrowskiDiffeomorphicFlows,
+ title = {{Diffeomorphic Explanations with Normalizing Flows}},
+ booktitle = {ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models},
+ author = {Dombrowski, Ann-Kathrin and Gerken, Jan E and Kessel, Pan}
+}
+
+@unpublished{JeanneretDiffusionExplanations,
+ title = {{Diffusion Models for Counterfactual Explanations}},
+ author = {Jeanneret, Guillaume and Simon, Lo\"\ic and Jurie, Frédéric},
+ arxivId = {2203.15636}
+}
+
+@article{RomerDoesSchwartz,
+ title = {{Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz}},
+ author = {Romer, Christina D and Romer, David H},
+ pages = {121--170},
+ volume = {4}
+}
+
+@article{CarrellDoesAchievement,
+ title = {{Does Your Cohort Matter? Measuring Peer Effects in College Achievement}},
+ author = {Carrell, Scott E and Fullerton, Richard L and West, James E},
+ number = {3},
+ pages = {439--464},
+ volume = {27}
+}
+
+@inproceedings{GalDropoutLearning,
+ title = {{Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning}},
+ booktitle = {International Conference on Machine Learning},
+ author = {Gal, Yarin and Ghahramani, Zoubin},
+ pages = {1050--1059},
+ publisher = {PMLR}
+}
+
+@article{SrivastavaDropout:Overfitting,
+ title = {{Dropout: A Simple Way to Prevent Neural Networks from Overfitting}},
+ author = {Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
+ number = {1},
+ pages = {1929--1958},
+ volume = {15}
+}
+
+@article{FangDynamicEvidence,
+ title = {{Dynamic Inefficiencies in an Employment-Based Health Insurance System: Theory and Evidence}},
+ author = {Fang, Hanming and Gavazza, Alessandro},
+ number = {7},
+ pages = {3047--3077},
+ volume = {101}
+}
+
+@article{GreeneEconometric71e,
+ title = {{Econometric Analysis, 71e}},
+ author = {Greene, William H}
+}
+
+@article{LucasEconometricHolland,
+ title = {{Econometric Policy Evaluation: A Critique `, in K. Brunner and A Meltzer, The Phillips Curve and Labor Markets, North Holland}},
+ author = {Lucas, J R}
+}
+
+@book{PerryEconomicAfter,
+ title = {{Economic Events, Ideas, and Policies: The 1960s and After}},
+ author = {Perry, George L and Tobin, James},
+ publisher = {Brookings Institution Press}
+}
+
+@article{GretherEconomicPhenomenon,
+ title = {{Economic Theory of Choice and the Preference Reversal Phenomenon}},
+ author = {Grether, David M and Plott, Charles R},
+ number = {4},
+ pages = {623--638},
+ volume = {69}
+}
+
+@article{VanBovenEgocentricEffect.,
+ title = {{Egocentric Empathy Gaps between Owners and Buyers: Misperceptions of the Endowment Effect.}},
+ author = {Van Boven, Leaf and Dunning, David and Loewenstein, George},
+ number = {1},
+ pages = {66},
+ volume = {79}
+}
+
+@inproceedings{AltmeyerEndogenousRecourse,
+ title = {{Endogenous Macrodynamics in Algorithmic Recourse}},
+ booktitle = {First IEEE Conference on Secure and Trustworthy Machine Learning},
+ author = {Altmeyer, Patrick and Angela, Giovan and Buszydlik, Aleksander and Dobiczek, Karol and van Deursen, Arie and Liem, Cynthia}
+}
+
+@article{XuEpidemiologicalInformation,
+ title = {{Epidemiological Data from the COVID-19 Outbreak, Real-Time Case Information}},
+ author = {Xu, Bo and Gutierrez, Bernardo and Mekaru, Sumiko and Sewalk, Kara and Goodwin, Lauren and Loskill, Alyssa and Cohn, Emily and Hswen, Yulin and Hill, Sarah C and Cobo, Maria M and Zarebski, Alexander and Li, Sabrina and Wu, Chieh-Hsi and Hulland, Erin and Morgan, Julia and Wang, Lin and O'Brien, Katelynn and Scarpino, Samuel V and Brownstein, John S and Pybus, Oliver G and Pigott, David M and Kraemer, Moritz U G},
+ number = {106},
+ volume = {7},
+ doi = {doi.org/10.1038/s41597-020-0448-0}
+}
+
+@article{QuEstimatingMatrix,
+ title = {{Estimating a Spatial Autoregressive Model with an Endogenous Spatial Weight Matrix}},
+ author = {Qu, Xi and Lee, Lung-fei},
+ number = {2},
+ pages = {209--232},
+ volume = {184}
+}
+
+@article{JohnssonEstimationApproach,
+ title = {{Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach}},
+ author = {Johnsson, Ida and Moon, Hyungsik Roger},
+ number = {2},
+ pages = {328--345},
+ volume = {103}
+}
+
+@inproceedings{NelsonEvaluatingAlgorithms,
+ title = {{Evaluating Model Drift in Machine Learning Algorithms}},
+ booktitle = {2015 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)},
+ author = {Nelson, Kevin and Corbin, George and Anania, Mark and Kovacs, Matthew and Tobias, Jeremy and Blowers, Misty},
+ pages = {1--8},
+ publisher = {IEEE}
+}
+
+@article{KahnemanExperimentalTheorem,
+ title = {{Experimental Tests of the Endowment Effect and the Coase Theorem}},
+ author = {Kahneman, Daniel and Knetsch, Jack L and Thaler, Richard H},
+ number = {6},
+ pages = {1325--1348},
+ volume = {98}
+}
+
+@article{ArrietaExplainableAI,
+ title = {{Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI}},
+ author = {Arrieta, Alejandro Barredo and Diaz-Rodriguez, Natalia and Del Ser, Javier and Bennetot, Adrien and Tabik, Siham and Barbado, Alberto and Garcia, Salvador and Gil-Lopez, Sergio and Molina, Daniel and Benjamins, Richard and {others}},
+ pages = {82--115},
+ volume = {58}
+}
+
+@article{CascarinoExplainableLearning,
+ title = {{Explainable Artificial Intelligence: Interpreting Default Forecasting Models Based on Machine Learning}},
+ author = {Cascarino, Giuseppe and Moscatelli, Mirko and Parlapiano, Fabio},
+ number = {674}
+}
+
+@unpublished{GoodfellowExplainingExamples,
+ title = {{Explaining and Harnessing Adversarial Examples}},
+ author = {Goodfellow, Ian J and Shlens, Jonathon and Szegedy, Christian},
+ arxivId = {1412.6572}
+}
+
+@inproceedings{MittelstadtExplainingAI,
+ title = {{Explaining Explanations in AI}},
+ booktitle = {Proceedings of the Conference on Fairness, Accountability, and Transparency},
+ author = {Mittelstadt, Brent and Russell, Chris and Wachter, Sandra},
+ pages = {279--288}
+}
+
+@inproceedings{MothilalExplainingExplanations,
+ title = {{Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations}},
+ booktitle = {Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency},
+ author = {Mothilal, Ramaravind K and Sharma, Amit and Tan, Chenhao},
+ pages = {607--617}
+}
+
+@article{MillerExplanationSciences,
+ title = {{Explanation in Artificial Intelligence: Insights from the Social Sciences}},
+ author = {Miller, Tim},
+ pages = {1--38},
+ volume = {267}
+}
+
+@article{DhurandharExplanationsNegatives,
+ title = {{Explanations Based on the Missing: Towards Contrastive Explanations with Pertinent Negatives}},
+ author = {Dhurandhar, Amit and Chen, Pin-Yu and Luss, Ronny and Tu, Chun-Chen and Ting, Paishun and Shanmugam, Karthikeyan and Das, Payel},
+ volume = {31}
+}
+
+@unpublished{KuiperExploringAuthorities,
+ title = {{Exploring Explainable AI in the Financial Sector: Perspectives of Banks and Supervisory Authorities}},
+ author = {Kuiper, Ouren and van den Berg, Martin and van den Burgt, Joost and Leijnen, Stefan},
+ arxivId = {2111.02244}
+}
+
+@inproceedings{PoyiadziFACE:Explanations,
+ title = {{FACE: Feasible and Actionable Counterfactual Explanations}},
+ booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
+ author = {Poyiadzi, Rafael and Sokol, Kacper and Santos-Rodriguez, Raul and De Bie, Tijl and Flach, Peter},
+ pages = {344--350}
+}
+
+@article{RabanserFailingShift,
+ title = {{Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift}},
+ author = {Rabanser, Stephan and G{\"{u}}nnemann, Stephan and Lipton, Zachary},
+ volume = {32}
+}
+
+@article{JohanssonFailureTask,
+ title = {{Failure to Detect Mismatches between Intention and Outcome in a Simple Decision Task}},
+ author = {Johansson, Petter and Hall, Lars and Sikstr{\"{o}}m, Sverker and Olsson, Andreas},
+ number = {5745},
+ pages = {116--119},
+ volume = {310}
+}
+
+@misc{BarocasFairnessLearning,
+ title = {{Fairness and Machine Learning}},
+ author = {Barocas, Solon and Hardt, Moritz and Narayanan, Arvind},
+ url = {https://fairmlbook.org/index.html}
+}
+
+@inproceedings{JabbariFairnessLearning,
+ title = {{Fairness in Reinforcement Learning}},
+ booktitle = {International Conference on Machine Learning},
+ author = {Jabbari, Shahin and Joseph, Matthew and Kearns, Michael and Morgenstern, Jamie and Roth, Aaron},
+ pages = {1617--1626},
+ publisher = {PMLR}
+}
+
+@unpublished{InnesFashionableFlux,
+ title = {{Fashionable Modelling with Flux}},
+ author = {Innes, Michael and Saba, Elliot and Fischer, Keno and Gandhi, Dhairya and Rudilosso, Marco Concetto and Joy, Neethu Mariya and Karmali, Tejan and Pal, Avik and Shah, Viral},
+ arxivId = {1811.01457}
+}
+
+@inproceedings{SatopaaFindingBehavior,
+ title = {{Finding a" Kneedle" in a Haystack: Detecting Knee Points in System Behavior}},
+ booktitle = {2011 31st International Conference on Distributed Computing Systems Workshops},
+ author = {Satopaa, Ville and Albrecht, Jeannie and Irwin, David and Raghavan, Barath},
+ pages = {166--171},
+ publisher = {IEEE}
+}
+
+@article{AuerFinite-TimeProblem,
+ title = {{Finite-Time Analysis of the Multiarmed Bandit Problem}},
+ author = {Auer, Peter and Cesa-Bianchi, Nicolo and Fischer, Paul},
+ number = {2},
+ pages = {235--256},
+ volume = {47}
+}
+
+@article{InnesFlux:Julia,
+ title = {{Flux: Elegant Machine Learning with Julia}},
+ author = {Innes, Mike},
+ number = {25},
+ pages = {602},
+ volume = {3}
+}
+
+@inproceedings{SlackFoolingMethods,
+ title = {{Fooling Lime and Shap: Adversarial Attacks on Post Hoc Explanation Methods}},
+ booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
+ author = {Slack, Dylan and Hilgard, Sophie and Jia, Emily and Singh, Sameer and Lakkaraju, Himabindu},
+ pages = {180--186}
+}
+
+@article{JosephForecastingUp,
+ title = {{Forecasting Uk Inflation Bottom Up}},
+ author = {Joseph, Andreas and Kalamara, Eleni and Kapetanios, George and Potjagailo, Galina}
+}
+
+@article{ZhangForecastingArt,
+ title = {{Forecasting with Artificial Neural Networks:: The State of the Art}},
+ author = {Zhang, Guoqiang and Patuwo, B Eddy and Hu, Michael Y},
+ number = {1},
+ pages = {35--62},
+ volume = {14}
+}
+
+@article{McCrackenFRED-MD:Research,
+ title = {{FRED-MD: A Monthly Database for Macroeconomic Research}},
+ author = {McCracken, Michael W and Ng, Serena},
+ number = {4},
+ pages = {574--589},
+ volume = {34}
+}
+
+@article{CarrellFromFormation,
+ title = {{From Natural Variation to Optimal Policy? The Importance of Endogenous Peer Group Formation}},
+ author = {Carrell, Scott E and Sacerdote, Bruce I and West, James E},
+ number = {3},
+ pages = {855--882},
+ volume = {81}
+}
+
+@inproceedings{RasmussenGaussianLearning,
+ title = {{Gaussian Processes in Machine Learning}},
+ booktitle = {Summer School on Machine Learning},
+ author = {Rasmussen, Carl Edward},
+ pages = {63--71},
+ publisher = {Springer}
+}
+
+@inproceedings{BuolamwiniGenderClassification,
+ title = {{Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification}},
+ booktitle = {Conference on Fairness, Accountability and Transparency},
+ author = {Buolamwini, Joy and Gebru, Timnit},
+ pages = {77--91},
+ publisher = {PMLR}
+}
+
+@article{CarrizosaGeneratingOptimization,
+ title = {{Generating Collective Counterfactual Explanations in Score-Based Classification via Mathematical Optimization}},
+ author = {Carrizosa, Emilio and Ramırez-Ayerbe, Jasone and Romero, Dolores}
+}
+
+@inproceedings{SchutGeneratingUncertainties,
+ title = {{Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties}},
+ booktitle = {International Conference on Artificial Intelligence and Statistics},
+ author = {Schut, Lisa and Key, Oscar and Mc Grath, Rory and Costabello, Luca and Sacaleanu, Bogdan and Gal, Yarin and {others}},
+ pages = {1756--1764},
+ publisher = {PMLR}
+}
+
+@misc{HoffmanGermanData,
+ title = {{German Credit Data}},
+ author = {Hoffman, Hans},
+ url = {https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)}
+}
+
+@misc{HoffmanGermanDatab,
+ title = {{German Credit Data}},
+ author = {Hoffman, Hans},
+ url = {https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data)}
+}
+
+@unpublished{AntoranGettingEstimates,
+ title = {{Getting a Clue: A Method for Explaining Uncertainty Estimates}},
+ author = {Antor{\'{a}}n, Javier and Bhatt, Umang and Adel, Tameem and Weller, Adrian and Hern{\'{a}}ndez-Lobato, José Miguel},
+ arxivId = {2006.06848}
+}
+
+@misc{KaggleGiveYears.,
+ title = {{Give Me Some Credit, Improve on the State of the Art in Credit Scoring by Predicting the Probability That Somebody Will Experience Financial Distress in the next Two Years.}},
+ author = {{Kaggle}},
+ publisher = {Kaggle},
+ url = {https://www.kaggle.com/c/GiveMeSomeCredit}
+}
+
+@misc{CompetitionGiveYears.,
+ title = {{Give Me Some Credit, Improve on the State of the Art in Credit Scoring by Predicting the Probability That Somebody Will Experience Financial Distress in the next Two Years.}},
+ author = {Competition, Kaggle},
+ url = {https://www.kaggle.com/c/GiveMeSomeCredit}
+}
+
+@article{MarkleGoalsDependence,
+ title = {{Goals as Reference Points in Marathon Running: A Novel Test of Reference Dependence}},
+ author = {Markle, Alex and Wu, George and White, Rebecca and Sackett, Aaron},
+ number = {1},
+ pages = {19--50},
+ volume = {56}
+}
+
+@unpublished{LachapelleGradient-BasedLearning,
+ title = {{Gradient-Based Neural Dag Learning}},
+ author = {Lachapelle, Sébastien and Brouillard, Philippe and Deleu, Tristan and Lacoste-Julien, Simon},
+ arxivId = {1906.02226}
+}
+
+@unpublished{JospinHands-onUsers,
+ title = {{Hands-on Bayesian Neural Networks–a Tutorial for Deep Learning Users}},
+ author = {Jospin, Laurent Valentin and Buntine, Wray and Boussaid, Farid and Laga, Hamid and Bennamoun, Mohammed},
+ arxivId = {2007.06823}
+}
+
+@article{UngemachHowDelay,
+ title = {{How Incidental Values from the Environment Affect Decisions about Money, Risk, and Delay}},
+ author = {Ungemach, Christoph and Stewart, Neil and Reimers, Stian},
+ number = {2},
+ pages = {253--260},
+ volume = {22}
+}
+
+@article{ManskiIdentificationProblem,
+ title = {{Identification of Endogenous Social Effects: The Reflection Problem}},
+ author = {Manski, Charles F},
+ number = {3},
+ pages = {531--542},
+ volume = {60}
+}
+
+@article{BramoulleIdentificationNetworks,
+ title = {{Identification of Peer Effects through Social Networks}},
+ author = {Bramoull{\'{e}}, Yann and Djebbari, Habiba and Fortin, Bernard},
+ number = {1},
+ pages = {41--55},
+ volume = {150}
+}
+
+@article{GilbertImmuneForecasting.,
+ title = {{Immune Neglect: A Source of Durability Bias in Affective Forecasting.}},
+ author = {Gilbert, Daniel T and Pinel, Elizabeth C and Wilson, Timothy D and Blumberg, Stephen J and Wheatley, Thalia P},
+ number = {3},
+ pages = {617},
+ volume = {75}
+}
+
+@article{HamzacebiImprovingForecasting,
+ title = {{Improving Artificial Neural Networks' Performance in Seasonal Time Series Forecasting}},
+ author = {Hamza{\c{c}}ebi, CoÅŸkun},
+ number = {23},
+ pages = {4550--4559},
+ volume = {178}
+}
+
+@unpublished{ImmerImprovingLinearization,
+ title = {{Improving Predictions of Bayesian Neural Networks via Local Linearization}},
+ author = {Immer, Alexander and Korzepa, Maciej and Bauer, Matthias},
+ arxivId = {2008.08400}
+}
+
+@article{HershfieldIncreasingSelf,
+ title = {{Increasing Saving Behavior through Age-Progressed Renderings of the Future Self}},
+ author = {Hershfield, Hal E and Goldstein, Daniel G and Sharpe, William F and Fox, Jesse and Yeykelis, Leo and Carstensen, Laura L and Bailenson, Jeremy N},
+ number = {SPL},
+ pages = {S23–S37},
+ volume = {48}
+}
+
+@article{AngelucciIndirectConsumption,
+ title = {{Indirect Effects of an Aid Program: How Do Cash Transfers Affect Ineligibles' Consumption?}},
+ author = {Angelucci, Manuela and De Giorgi, Giacomo},
+ number = {1},
+ pages = {486--508},
+ volume = {99}
+}
+
+@article{AbadieInstrumentalEarnings,
+ title = {{Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings}},
+ author = {Abadie, Alberto and Angrist, Joshua and Imbens, Guido},
+ number = {1},
+ pages = {91--117},
+ volume = {70}
+}
+
+@book{MolnarInterpretableLearning,
+ title = {{Interpretable Machine Learning}},
+ author = {Molnar, Christoph},
+ publisher = {Lulu. com}
+}
+
+@unpublished{Ish-HorowiczInterpretingImportance,
+ title = {{Interpreting Deep Neural Networks through Variable Importance}},
+ author = {Ish-Horowicz, Jonathan and Udwin, Dana and Flaxman, Seth and Filippi, Sarah and Crawford, Lorin},
+ arxivId = {1901.09839}
+}
+
+@inproceedings{KaurInterpretingLearning,
+ title = {{Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning}},
+ booktitle = {Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
+ author = {Kaur, Harmanpreet and Nori, Harsha and Jenkins, Samuel and Caruana, Rich and Wallach, Hanna and Wortman Vaughan, Jennifer},
+ pages = {1--14}
+}
+
+@unpublished{SzegedyIntriguingNetworks,
+ title = {{Intriguing Properties of Neural Networks}},
+ author = {Szegedy, Christian and Zaremba, Wojciech and Sutskever, Ilya and Bruna, Joan and Erhan, Dumitru and Goodfellow, Ian and Fergus, Rob},
+ arxivId = {1312.6199}
+}
+
+@book{ManningIntroductionRetrieval,
+ title = {{Introduction to Information Retrieval}},
+ author = {Manning, Christopher D and Sch{\"{u}}tze, Hinrich and Raghavan, Prabhakar},
+ publisher = {Cambridge university press}
+}
+
+@book{SchutzeIntroductionRetrieval,
+ title = {{Introduction to Information Retrieval}},
+ author = {Sch{\"{u}}tze, Hinrich and Manning, Christopher D and Raghavan, Prabhakar},
+ volume = {39},
+ publisher = {Cambridge University Press Cambridge}
+}
+
+@unpublished{LaugelInverseLearning,
+ title = {{Inverse Classification for Comparison-Based Interpretability in Machine Learning}},
+ author = {Laugel, Thibault and Lesot, Marie-Jeanne and Marsala, Christophe and Renard, Xavier and Detyniecki, Marcin},
+ arxivId = {1712.08443}
+}
+
+@article{DaxbergerLaplaceLearning,
+ title = {{Laplace Redux-Effortless Bayesian Deep Learning}},
+ author = {Daxberger, Erik and Kristiadi, Agustinus and Immer, Alexander and Eschenhagen, Runa and Bauer, Matthias and Hennig, Philipp},
+ volume = {34}
+}
+
+@article{WidmerLearningContexts,
+ title = {{Learning in the Presence of Concept Drift and Hidden Contexts}},
+ author = {Widmer, Gerhard and Kubat, Miroslav},
+ number = {1},
+ pages = {69--101},
+ volume = {23}
+}
+
+@inproceedings{StutzLearningClassifiers,
+ title = {{Learning Optimal Conformal Classifiers}},
+ author = {Stutz, David and Dvijotham, Krishnamurthy Dj and Cemgil, Ali Taylan and Doucet, Arnaud},
+ url = {https://openreview.net/forum?id=t8O-4LKFVx},
+ language = {en}
+}
+
+@article{SadinleLeastLevels,
+ title = {{Least Ambiguous Set-Valued Classifiers with Bounded Error Levels}},
+ author = {Sadinle, Mauricio and Lei, Jing and Wasserman, Larry},
+ number = {525},
+ pages = {223--234},
+ volume = {114},
+ publisher = {Taylor {\&} Francis}
+}
+
+@article{SunsteinLibertarianOxymoron,
+ title = {{Libertarian Paternalism Is Not an Oxymoron}},
+ author = {Sunstein, Cass R and Thaler, Richard H},
+ pages = {1159--1202}
+}
+
+@article{AngristLifetimeRecords,
+ title = {{Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records}},
+ author = {Angrist, Joshua D},
+ pages = {313--336}
+}
+
+@article{HochreiterLongMemory,
+ title = {{Long Short-Term Memory}},
+ author = {Hochreiter, Sepp and Schmidhuber, Jürgen},
+ number = {8},
+ pages = {1735--1780},
+ volume = {9}
+}
+
+@article{MasiniMachineForecasting,
+ title = {{Machine Learning Advances for Time Series Forecasting}},
+ author = {Masini, Ricardo P and Medeiros, Marcelo C and Mendes, Eduardo F}
+}
+
+@inproceedings{AckermanMachineSlices,
+ title = {{Machine Learning Model Drift Detection Via Weak Data Slices}},
+ booktitle = {2021 IEEE/ACM Third International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest)},
+ author = {Ackerman, Samuel and Dube, Parijat and Farchi, Eitan and Raz, Orna and Zalmanovici, Marcel},
+ pages = {1--8},
+ publisher = {IEEE}
+}
+
+@article{BorchMachineTrading,
+ title = {{Machine Learning, Knowledge Risk, and Principal-Agent Problems in Automated Trading}},
+ author = {Borch, Christian},
+ pages = {101852}
+}
+
+@book{MurphyMachinePerspective,
+ title = {{Machine Learning: A Probabilistic Perspective}},
+ author = {Murphy, Kevin P},
+ publisher = {MIT press}
+}
+
+@article{JacksonMeetingNetworks,
+ title = {{Meeting Strangers and Friends of Friends: How Random Are Social Networks?}},
+ author = {Jackson, Matthew O and Rogers, Brian W},
+ number = {3},
+ pages = {890--915},
+ volume = {97}
+}
+
+@book{PindyckMicroeconomics,
+ title = {{Microeconomics}},
+ author = {Pindyck, Robert S and Rubinfeld, Daniel L},
+ publisher = {Pearson Education}
+}
+
+@misc{CardMinimumPennsylvania,
+ title = {{Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania}},
+ author = {Card, David and Krueger, Alan B},
+ institution = {National Bureau of Economic Research}
+}
+
+@article{BlaomMLJ:Learning,
+ title = {{MLJ: A Julia Package for Composable Machine Learning}},
+ shorttitle = {MLJ},
+ author = {Blaom, Anthony D and Kiraly, Franz and Lienart, Thibaut and Simillides, Yiannis and Arenas, Diego and Vollmer, Sebastian J},
+ number = {55},
+ pages = {2704},
+ volume = {5},
+ url = {https://joss.theoj.org/papers/10.21105/joss.02704},
+ doi = {10.21105/joss.02704},
+ issn = {2475-9066}
+}
+
+@article{VerstyukModelingNetworks,
+ title = {{Modeling Multivariate Time Series in Economics: From Auto-Regressions to Recurrent Neural Networks}},
+ author = {Verstyuk, Sergiy}
+}
+
+@article{HartlandMulti-ArmedMeta-Bandits,
+ title = {{Multi-Armed Bandit, Dynamic Environments and Meta-Bandits}},
+ author = {Hartland, Cédric and Gelly, Sylvain and Baskiotis, Nicolas and Teytaud, Olivier and Sebag, Michele}
+}
+
+@article{HseeMusicValue.,
+ title = {{Music, Pandas, and Muggers: On the Affective Psychology of Value.}},
+ author = {Hsee, Christopher K and Rottenstreich, Yuval},
+ number = {1},
+ pages = {23},
+ volume = {133}
+}
+
+@unpublished{GriffithNameData,
+ title = {{Name Your Friends, but Only Five? The Importance of Censoring in Peer Effects Estimates Using Social Network Data}},
+ author = {Griffith, Alan}
+}
+
+@article{ListNeoclassicalMarketplace,
+ title = {{Neoclassical Theory versus Prospect Theory: Evidence from the Marketplace}},
+ author = {List, John A},
+ number = {2},
+ pages = {615--625},
+ volume = {72}
+}
+
+@article{BarabasiNetworkScience,
+ title = {{Network Science}},
+ author = {Barab{\'{a}}si, Albert-László}
+}
+
+@unpublished{BussmannNeuralData,
+ title = {{Neural Additive Vector Autoregression Models for Causal Discovery in Time Series Data}},
+ author = {Bussmann, Bart and Nys, Jannes and Latr{\'{e}}, Steven},
+ arxivId = {2010.09429}
+}
+
+@inproceedings{DorffnerNeuralProcessing,
+ title = {{Neural Networks for Time Series Processing}},
+ booktitle = {Neural Network World},
+ author = {Dorffner, Georg},
+ publisher = {Citeseer}
+}
+
+@book{LutkepohlNewAnalysis,
+ title = {{New Introduction to Multiple Time Series Analysis}},
+ author = {L{\"{u}}tkepohl, Helmut},
+ publisher = {Springer Science {\&} Business Media}
+}
+
+@book{BrockNonlinearEvidence,
+ title = {{Nonlinear Dynamics, Chaos, and Instability: Statistical Theory and Economic Evidence}},
+ author = {Brock, William Allen and Brock, William A and Hsieh, David Arthur and LeBaron, Blake Dean and Brock, William E},
+ publisher = {MIT press}
+}
+
+@book{NocedalNumericalOptimization,
+ title = {{Numerical Optimization}},
+ author = {Nocedal, Jorge and Wright, Stephen},
+ publisher = {Springer Science {\&} Business Media}
+}
+
+@unpublished{FanOnNetworks,
+ title = {{On Interpretability of Artificial Neural Networks}},
+ author = {Fan, Fenglei and Xiong, Jinjun and Wang, Ge},
+ arxivId = {2001.02522}
+}
+
+@article{ArconesOnStatistics,
+ title = {{On the Bootstrap of U and V Statistics}},
+ author = {Arcones, Miguel A and Gine, Evarist},
+ pages = {655--674}
+}
+
+@article{GalizziOnStudy,
+ title = {{On the External Validity of Social Preference Games: A Systematic Lab-Field Study}},
+ author = {Galizzi, Matteo M and Navarro-Martinez, Daniel},
+ number = {3},
+ pages = {976--1002},
+ volume = {65}
+}
+
+@unpublished{GarivierOnProblems,
+ title = {{On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems}},
+ author = {Garivier, Aurélien and Moulines, Eric},
+ arxivId = {0805.3415}
+}
+
+@article{ZhuOptimalRegression,
+ title = {{Optimal Subsampling Approaches for Large Sample Linear Regression}},
+ author = {Zhu, Rong and Ma, Ping and Mahoney, Michael W and Yu, Bin},
+ pages = {arXiv–1509}
+}
+
+@article{WangOptimalRegression,
+ title = {{Optimal Subsampling for Large Sample Logistic Regression}},
+ author = {Wang, HaiYing and Zhu, Rong and Ma, Ping},
+ number = {522},
+ pages = {829--844},
+ volume = {113}
+}
+
+@article{AltmeyerOptionEvaluation,
+ title = {{Option Pricing in the Heston Stochastic Volatility Model: An Empirical Evaluation}},
+ author = {Altmeyer, Patrick and Grapendal, Jacob Daniel and Pravosud, Makar and Quintana, Gand Derry}
+}
+
+@book{BishopPatternLearning,
+ title = {{Pattern Recognition and Machine Learning}},
+ author = {Bishop, Christopher M},
+ publisher = {springer}
+}
+
+@article{BramoullePeerSurvey,
+ title = {{Peer Effects in Networks: A Survey}},
+ author = {Bramoull{\'{e}}, Yann and Djebbari, Habiba and Fortin, Bernard},
+ pages = {603--629},
+ volume = {12}
+}
+
+@article{SacerdotePeerRoommates,
+ title = {{Peer Effects with Random Assignment: Results for Dartmouth Roommates}},
+ author = {Sacerdote, Bruce},
+ number = {2},
+ pages = {681--704},
+ volume = {116}
+}
+
+@article{BarberPredictiveJackknife+,
+ title = {{Predictive inference with the jackknife+}},
+ author = {Barber, Rina Foygel and Cand{\`{e}}s, Emmanuel J and Ramdas, Aaditya and Tibshirani, Ryan J},
+ number = {1},
+ pages = {486--507},
+ volume = {49},
+ publisher = {Institute of Mathematical Statistics},
+ url = {https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-1/Predictive-inference-with-the-jackknife/10.1214/20-AOS1965.full},
+ doi = {10.1214/20-AOS1965},
+ issn = {0090-5364, 2168-8966},
+ keywords = {62F40, 62G08, 62G09, conformal inference, cross-validation, distribution-free, jackknife, leave-one-out, stability}
+}
+
+@book{MurphyProbabilisticIntroduction,
+ title = {{Probabilistic Machine Learning: An Introduction}},
+ author = {Murphy, Kevin P},
+ publisher = {MIT Press}
+}
+
+@article{PawelczykProbabilisticallyRecourse,
+ title = {{Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse}},
+ shorttitle = {Probabilistically Robust Recourse},
+ author = {Pawelczyk, Martin and Datta, Teresa and van-den-Heuvel, Johannes and Kasneci, Gjergji and Lakkaraju, Himabindu}
+}
+
+@article{KahnemanProspectRisk,
+ title = {{Prospect Theory: An Analysis of Decision under Risk}},
+ author = {Kahneman, Daniel and Tversky, Amos},
+ pages = {263--291}
+}
+
+@article{CarlisleRacistControversy,
+ title = {{Racist Data Destruction? - a Boston Housing Dataset Controversy}},
+ author = {Carlisle, M},
+ url = {https://medium.com/@docintangible/racist-data-destruction-113e3eff54a8}
+}
+
+@inproceedings{HoRandomForests,
+ title = {{Random Decision Forests}},
+ booktitle = {Proceedings of 3rd International Conference on Document Analysis and Recognition},
+ author = {Ho, Tin Kam},
+ pages = {278--282},
+ volume = {1},
+ publisher = {IEEE}
+}
+
+@article{ShafirReason-BasedChoice,
+ title = {{Reason-Based Choice}},
+ author = {Shafir, Eldar and Simonson, Itamar and Tversky, Amos},
+ number = {1-2},
+ pages = {11--36},
+ volume = {49}
+}
+
+@article{KahnemanReferenceFeelings,
+ title = {{Reference Points, Anchors, Norms, and Mixed Feelings}},
+ author = {Kahneman, Daniel},
+ number = {2},
+ pages = {296--312},
+ volume = {51}
+}
+
+@article{AllenReference-DependentRunners,
+ title = {{Reference-Dependent Preferences: Evidence from Marathon Runners}},
+ author = {Allen, Eric J and Dechow, Patricia M and Pope, Devin G and Wu, George},
+ number = {6},
+ pages = {1657--1672},
+ volume = {63}
+}
+
+@article{denHengstReinforcementReview,
+ title = {{Reinforcement Learning for Personalization: A Systematic Literature Review}},
+ author = {den Hengst, Floris and Grua, Eoin Martino and el Hassouni, Ali and Hoogendoorn, Mark},
+ number = {Preprint},
+ pages = {1--41}
+}
+
+@book{SuttonReinforcementIntroduction,
+ title = {{Reinforcement Learning: An Introduction}},
+ author = {Sutton, Richard S and Barto, Andrew G},
+ publisher = {MIT press}
+}
+
+@book{BerlinetReproducingStatistics,
+ title = {{Reproducing Kernel Hilbert Spaces in Probability and Statistics}},
+ author = {Berlinet, Alain and Thomas-Agnan, Christine},
+ publisher = {Springer Science {\&} Business Media}
+}
+
+@article{HamonRobustnessIntelligence,
+ title = {{Robustness and Explainability of Artificial Intelligence}},
+ author = {Hamon, Ronan and Junklewitz, Henrik and Sanchez, Ignacio}
+}
+
+@article{PopeRoundLab,
+ title = {{Round Numbers as Goals: Evidence from Baseball, SAT Takers, and the Lab}},
+ author = {Pope, Devin and Simonsohn, Uri},
+ number = {1},
+ pages = {71--79},
+ volume = {22}
+}
+
+@article{ThalerSaveSaving,
+ title = {{Save More Tomorrow: Using Behavioral Economics to Increase Employee Saving}},
+ author = {Thaler, Richard H and Benartzi, Shlomo},
+ number = {S1},
+ pages = {S164–S187},
+ volume = {112}
+}
+
+@article{PedregosaScikit-Learn:Python,
+ title = {{Scikit-Learn: Machine Learning in Python}},
+ author = {Pedregosa, Fabian and Varoquaux, Gaël and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and {others}},
+ pages = {2825--2830},
+ volume = {12}
+}
+
+@article{KihoroSeasonalModels,
+ title = {{Seasonal Time Series Forecasting: A Comparative Study of ARIMA and ANN Models}},
+ author = {Kihoro, J and Otieno, R O and Wafula, C}
+}
+
+@unpublished{LakshminarayananSimpleEnsembles,
+ title = {{Simple and Scalable Predictive Uncertainty Estimation Using Deep Ensembles}},
+ author = {Lakshminarayanan, Balaji and Pritzel, Alexander and Blundell, Charles},
+ arxivId = {1612.01474}
+}
+
+@article{Goldsmith-PinkhamSocialEffects,
+ title = {{Social Networks and the Identification of Peer Effects}},
+ author = {Goldsmith-Pinkham, Paul and Imbens, Guido W},
+ number = {3},
+ pages = {253--264},
+ volume = {31}
+}
+
+@article{ThalerSomeInconsistency,
+ title = {{Some Empirical Evidence on Dynamic Inconsistency}},
+ author = {Thaler, Richard},
+ number = {3},
+ pages = {201--207},
+ volume = {8}
+}
+
+@article{PaceSparseAutoregressions,
+ title = {{Sparse Spatial Autoregressions}},
+ author = {Pace, R Kelley and Barry, Ronald},
+ number = {3},
+ pages = {291--297},
+ volume = {33}
+}
+
+@article{BesbesStochasticRewards,
+ title = {{Stochastic Multi-Armed-Bandit Problem with Non-Stationary Rewards}},
+ author = {Besbes, Omar and Gur, Yonatan and Zeevi, Assaf},
+ pages = {199--207},
+ volume = {27}
+}
+
+@article{RudinStopInstead,
+ title = {{Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead}},
+ author = {Rudin, Cynthia},
+ number = {5},
+ pages = {206--215},
+ volume = {1}
+}
+
+@inproceedings{MillerStrategicDisguise,
+ title = {{Strategic Classification Is Causal Modeling in Disguise}},
+ booktitle = {Proceedings of the 37th International Conference on Machine Learning},
+ author = {Miller, John and Milli, Smitha and Hardt, Moritz},
+ pages = {6917--6926},
+ publisher = {PMLR},
+ url = {https://proceedings.mlr.press/v119/miller20b.html},
+ issn = {2640-3498}
+}
+
+@book{KilianStructuralAnalysis,
+ title = {{Structural Vector Autoregressive Analysis}},
+ author = {Kilian, Lutz and L{\"{u}}tkepohl, Helmut},
+ publisher = {Cambridge University Press}
+}
+
+@article{CortesSupport-VectorNetworks,
+ title = {{Support-Vector Networks}},
+ author = {Cortes, Corinna and Vapnik, Vladimir},
+ number = {3},
+ pages = {273--297},
+ volume = {20}
+}
+
+@unpublished{RajTamingApproach,
+ title = {{Taming Non-Stationary Bandits: A Bayesian Approach}},
+ author = {Raj, Vishnu and Kalyani, Sheetal},
+ arxivId = {1707.09727}
+}
+
+@book{PearlTheEffect,
+ title = {{The Book of Why: The New Science of Cause and Effect}},
+ author = {Pearl, Judea and Mackenzie, Dana},
+ publisher = {Basic books}
+}
+
+@unpublished{WilsonTheLearning,
+ title = {{The Case for Bayesian Deep Learning}},
+ author = {Wilson, Andrew Gordon},
+ arxivId = {2001.10995}
+}
+
+@article{YehTheClients,
+ title = {{The Comparisons of Data Mining Techniques for the Predictive Accuracy of Probability of Default of Credit Card Clients}},
+ author = {Yeh, I-Cheng and Lien, Che-hui},
+ number = {2},
+ pages = {2473--2480},
+ volume = {36}
+}
+
+@article{AbadieTheCountry,
+ title = {{The Economic Costs of Conflict: A Case Study of the Basque Country}},
+ author = {Abadie, Alberto and Gardeazabal, Javier},
+ number = {1},
+ pages = {113--132},
+ volume = {93}
+}
+
+@article{HseeTheAlternatives,
+ title = {{The Evaluability Hypothesis: An Explanation for Preference Reversals between Joint and Separate Evaluations of Alternatives}},
+ author = {Hsee, Christopher K},
+ number = {3},
+ pages = {247--257},
+ volume = {67}
+}
+
+@misc{BernankeTheTransnission,
+ title = {{The Federal Funds Rate and the Channels of Monetary Transnission}},
+ author = {Bernanke, Ben S},
+ publisher = {National Bureau of Economic Research Cambridge, Mass., USA}
+}
+
+@article{LernerTheSadness,
+ title = {{The Financial Costs of Sadness}},
+ author = {Lerner, Jennifer S and Li, Ye and Weber, Elke U},
+ number = {1},
+ pages = {72--79},
+ volume = {24}
+}
+
+@article{TverskyTheChoice,
+ title = {{The Framing of Decisions and the Psychology of Choice}},
+ author = {Tversky, Amos and Kahneman, Daniel},
+ number = {4481},
+ pages = {453--458},
+ volume = {211}
+}
+
+@techreport{ChouldechovaTheLearning,
+ title = {{The Frontiers of Fairness in Machine Learning}},
+ author = {Chouldechova, Alexandra and Roth, Aaron},
+ url = {http://arxiv.org/abs/1810.08810},
+ institution = {arXiv},
+ doi = {10.48550/arXiv.1810.08810},
+ keywords = {Computer Science - Computer Science and Game Theory, Computer Science - Data Structures and Algorithms, Computer Science - Machine Learning, Statistics - Machine Learning}
+}
+
+@article{BholatTheBanking,
+ title = {{The Impact of Covid on Machine Learning and Data Science in UK Banking}},
+ author = {Bholat, D and Gharbawi, M and Thew, O}
+}
+
+@article{GoodfriendTheDisinflation,
+ title = {{The Incredible Volcker Disinflation}},
+ author = {Goodfriend, Marvin and King, Robert G},
+ number = {5},
+ pages = {981--1015},
+ volume = {52}
+}
+
+@unpublished{BastounisTheNetworks,
+ title = {{The Mathematics of Adversarial Attacks in AI–Why Deep Learning Is Unstable despite the Existence of Stable Neural Networks}},
+ author = {Bastounis, Alexander and Hansen, Anders C and Vla{\v{c}}i{\'{c}}, Verner},
+ arxivId = {2109.06098}
+}
+
+@unpublished{ParrTheLearning,
+ title = {{The Matrix Calculus You Need for Deep Learning}},
+ author = {Parr, Terence and Howard, Jeremy},
+ arxivId = {1802.01528}
+}
+
+@article{LeCunTheDigits,
+ title = {{The MNIST Database of Handwritten Digits}},
+ author = {LeCun, Yann}
+}
+
+@article{MischelTheGratification.,
+ title = {{The Nature of Adolescent Competencies Predicted by Preschool Delay of Gratification.}},
+ author = {Mischel, Walter and Shoda, Yuichi and Peake, Philip K},
+ number = {4},
+ pages = {687},
+ volume = {54}
+}
+
+@article{DellTheMita,
+ title = {{The Persistent Effects of Peru's Mining Mita}},
+ author = {Dell, Melissa},
+ number = {6},
+ pages = {1863--1903},
+ volume = {78}
+}
+
+@article{MadrianTheBehavior,
+ title = {{The Power of Suggestion: Inertia in 401 (k) Participation and Savings Behavior}},
+ author = {Madrian, Brigitte C and Shea, Dennis F},
+ number = {4},
+ pages = {1149--1187},
+ volume = {116}
+}
+
+@article{PearlTheLearning,
+ title = {{The Seven Tools of Causal Inference, with Reflections on Machine Learning}},
+ author = {Pearl, Judea},
+ number = {3},
+ pages = {54--60},
+ volume = {62}
+}
+
+@article{EpsteinTheTime.,
+ title = {{The Stability of Behavior: I. On Predicting Most of the People Much of the Time.}},
+ author = {Epstein, Seymour},
+ number = {7},
+ pages = {1097},
+ volume = {37}
+}
+
+@article{GneezyTheOutcome,
+ title = {{The Uncertainty Effect: When a Risky Prospect Is Valued Less than Its Worst Possible Outcome}},
+ author = {Gneezy, Uri and List, John A and Wu, George},
+ number = {4},
+ pages = {1283--1309},
+ volume = {121}
+}
+
+@article{HansenTheTrading,
+ title = {{The Virtue of Simplicity: On Machine Learning Models in Algorithmic Trading}},
+ author = {Hansen, Kristian Bondo},
+ number = {1},
+ pages = {2053951720926558},
+ volume = {7}
+}
+
+@inproceedings{GuptaThompsonBandits,
+ title = {{Thompson Sampling for Dynamic Multi-Armed Bandits}},
+ booktitle = {2011 10th International Conference on Machine Learning and Applications and Workshops},
+ author = {Gupta, Neha and Granmo, Ole-Christoffer and Agrawala, Ashok},
+ pages = {484--489},
+ volume = {1},
+ publisher = {IEEE}
+}
+
+@book{HamiltonTimeAnalysis,
+ title = {{Time Series Analysis}},
+ author = {Hamilton, James Douglas},
+ publisher = {Princeton university press}
+}
+
+@article{ZhangTimeModel,
+ title = {{Time Series Forecasting Using a Hybrid ARIMA and Neural Network Model}},
+ author = {Zhang, G Peter},
+ pages = {159--175},
+ volume = {50}
+}
+
+@article{KydlandTimeFluctuations,
+ title = {{Time to Build and Aggregate Fluctuations}},
+ author = {Kydland, Finn E and Prescott, Edward C},
+ pages = {1345--1370}
+}
+
+@article{ArielyTomValue,
+ title = {{Tom Sawyer and the Construction of Value}},
+ author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
+ number = {1},
+ pages = {1--10},
+ volume = {60}
+}
+
+@inproceedings{CarliniTowardsNetworks,
+ title = {{Towards Evaluating the Robustness of Neural Networks}},
+ booktitle = {2017 Ieee Symposium on Security and Privacy (Sp)},
+ author = {Carlini, Nicholas and Wagner, David},
+ pages = {39--57},
+ publisher = {IEEE}
+}
+
+@unpublished{JoshiTowardsSystems,
+ title = {{Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems}},
+ author = {Joshi, Shalmali and Koyejo, Oluwasanmi and Vijitbenjaronk, Warut and Kim, Been and Ghosh, Joydeep},
+ arxivId = {1907.09615}
+}
+
+@unpublished{UpadhyayTowardsRecourse,
+ title = {{Towards Robust and Reliable Algorithmic Recourse}},
+ author = {Upadhyay, Sohini and Joshi, Shalmali and Lakkaraju, Himabindu},
+ arxivId = {2102.13620}
+}
+
+@book{VarshneyTrustworthyLearning,
+ title = {{Trustworthy Machine Learning}},
+ author = {Varshney, Kush R},
+ publisher = {Independently Published}
+}
+
+@misc{AngelopoulosUncertaintyPrediction,
+ title = {{Uncertainty Sets for Image Classifiers Using Conformal Prediction}},
+ author = {Angelopoulos, Anastasios and Bates, Stephen and Malik, Jitendra and Jordan, Michael I},
+ number = {arXiv:2009.14193},
+ publisher = {arXiv},
+ url = {http://arxiv.org/abs/2009.14193},
+ arxivId = {2009.14193},
+ keywords = {Computer Science - Computer Vision and Pattern Recognition, Mathematics - Statistics Theory, Statistics - Machine Learning}
+}
+
+@article{NagelUnravelingStudy,
+ title = {{Unraveling in Guessing Games: An Experimental Study}},
+ author = {Nagel, Rosemarie},
+ number = {5},
+ pages = {1313--1326},
+ volume = {85}
+}
+
+@article{PfaffVARVars,
+ title = {{VAR, SVAR and SVEC Models: Implementation within R Package Vars}},
+ author = {Pfaff, Bernhard and {others}},
+ number = {4},
+ pages = {1--32},
+ volume = {27}
+}
+
+@article{CrawfordVariableStudy,
+ title = {{Variable Prioritization in Nonlinear Black Box Methods: A Genetic Association Case Study}},
+ author = {Crawford, Lorin and Flaxman, Seth R and Runcie, Daniel E and West, Mike},
+ number = {2},
+ pages = {958},
+ volume = {13}
+}
+
+@misc{LawrenceVariationalModels,
+ title = {{Variational Inference in Probabilistic Models}},
+ author = {Lawrence, Neil David},
+ institution = {University of Cambridge}
+}
+
+@article{MigutVisualizing2D,
+ title = {{Visualizing Multi-Dimensional Decision Boundaries in 2D}},
+ author = {Migut, M A and Worring, Marcel and Veenman, Cor J},
+ number = {1},
+ pages = {273--295},
+ volume = {29}
+}
+
+@book{ONeilWeaponsDemocracy,
+ title = {{Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy}},
+ author = {O'Neil, Cathy},
+ publisher = {Crown}
+}
+
+@inproceedings{BlundellWeightNetwork,
+ title = {{Weight Uncertainty in Neural Network}},
+ booktitle = {International Conference on Machine Learning},
+ author = {Blundell, Charles and Cornebise, Julien and Kavukcuoglu, Koray and Wierstra, Daan},
+ pages = {1613--1622},
+ publisher = {PMLR}
+}
+
+@unpublished{KendallWhatVision,
+ title = {{What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?}},
+ author = {Kendall, Alex and Gal, Yarin},
+ arxivId = {1703.04977}
+}
+
+@article{SlovicWhoAxiom,
+ title = {{Who Accepts Savage's Axiom?}},
+ author = {Slovic, Paul and Tversky, Amos},
+ number = {6},
+ pages = {368--373},
+ volume = {19}
+}
+
+@unpublished{GrinsztajnWhyData,
+ title = {{Why Do Tree-Based Models Still Outperform Deep Learning on Tabular Data?}},
+ author = {Grinsztajn, Léo and Oyallon, Edouard and Varoquaux, Gaël},
+ arxivId = {2207.08815}
+}
+
+@inproceedings{GrathwohlYourOne,
+ title = {{Your classifier is secretly an energy based model and you should treat it like one}},
+ author = {Grathwohl, Will and Wang, Kuan-Chieh and Jacobsen, Joern-Henrik and Duvenaud, David and Norouzi, Mohammad and Swersky, Kevin},
+ url = {https://openreview.net/forum?id=Hkxzx0NtDB},
+ language = {en}
+}
+
+@article{ArielyCoherentPreferences,
+ title = {{``Coherent Arbitrariness'': Stable Demand Curves without Stable Preferences}},
+ author = {Ariely, Dan and Loewenstein, George and Prelec, Drazen},
+ number = {1},
+ pages = {73--106},
+ volume = {118}
+}
\ No newline at end of file