updated README

README.md

@@ -3,15 +3,21 @@
 
 This repository contains all code, notebooks, data and empirical results
 for our conference paper “Endogenous Macrodynamics in Algorithmic
-Recourse”. Below is a list of relevant resources hosted in this
-repository:
+Recourse” (Altmeyer et al. 2023).
 
-1.  [Paper](paper/paper.pdf)
-2.  [Online
+Below is a list of relevant resources hosted in this repository:
+
+1.  [Paper](paper/paper.pdf) in this repo
+2.  [Paper](https://openreview.net/pdf?id=-LFT2YicI9v) on OpenReview
+3.  [Online
     Companion](https://www.paltmeyer.com/endogenous-macrodynamics-in-algorithmic-recourse/)
-3.  [IEEE SaTML Presentation
+4.  [IEEE SaTML Presentation
     Slides](https://www.paltmeyer.com/content/talks/posts/2023-ieee-satml/presentation.html)
-4.  [IEEE SaTML Poster](dev/poster/poster.pdf)
+5.  [IEEE SaTML Poster](dev/poster/poster.pdf)
+6.  Software:
+    [`AlgorithmicRecourseDynamics.jl`](https://github.com/pat-alt/AlgorithmicRecourseDynamics.jl)
+    and
+    [`CounterfactualExplanations.jl`](https://github.com/pat-alt/CounterfactualExplanations.jl)
 
 ## Motivation
 
@@ -73,3 +79,18 @@ the Gravitational generator the counterfactual ends up all the way
 inside the target domain. Find out more in the [paper](paper/paper.pdf).
 
 ![](paper/www/mitigation.png)
+
+## References
+
+<div id="refs" class="references csl-bib-body hanging-indent">
+
+<div id="ref-altmeyer2023endogenous" class="csl-entry">
+
+Altmeyer, Patrick, Giovan Angela, Aleksander Buszydlik, Karol Dobiczek,
+Arie van Deursen, and Cynthia Liem. 2023. “Endogenous Macrodynamics in
+Algorithmic Recourse.” In *First IEEE Conference on Secure and
+Trustworthy Machine Learning*.
+
+</div>
+
+</div>

README.qmd

 ---
 format: commonmark
+bibliography: bib.bib
 ---
 
 # Endogenous Macrodynamics in Algorithmic Recourse
 
-This repository contains all code, notebooks, data and empirical results for our conference paper "Endogenous Macrodynamics in Algorithmic Recourse". Below is a list of relevant resources hosted in this repository:
+This repository contains all code, notebooks, data and empirical results for our conference paper "Endogenous Macrodynamics in Algorithmic Recourse" [@altmeyer2023endogenous]. 
 
-1. [Paper](paper/paper.pdf)
-2. [Online Companion](https://www.paltmeyer.com/endogenous-macrodynamics-in-algorithmic-recourse/)
-3. [IEEE SaTML Presentation Slides](https://www.paltmeyer.com/content/talks/posts/2023-ieee-satml/presentation.html)
-4. [IEEE SaTML Poster](dev/poster/poster.pdf)
+Below is a list of relevant resources hosted in this repository:
+
+1. [Paper](paper/paper.pdf) in this repo 
+2. [Paper](https://openreview.net/pdf?id=-LFT2YicI9v) on OpenReview
+3. [Online Companion](https://www.paltmeyer.com/endogenous-macrodynamics-in-algorithmic-recourse/)
+4. [IEEE SaTML Presentation Slides](https://www.paltmeyer.com/content/talks/posts/2023-ieee-satml/presentation.html)
+5. [IEEE SaTML Poster](dev/poster/poster.pdf)
+6. Software: [`AlgorithmicRecourseDynamics.jl`](https://github.com/pat-alt/AlgorithmicRecourseDynamics.jl) and [`CounterfactualExplanations.jl`](https://github.com/pat-alt/CounterfactualExplanations.jl)
 
 ## Motivation
 
@@ -33,3 +38,5 @@ Existing work on Counterfactual Explanations (CE) and Algorithmic Recourse (AR)
 By introducing a second penalty term in the counterfactual search objective, we can explicitly penalize external costs. The figure below illustrates how the mitigation strategies compared to the baseline approach, that is, Wachter (Generic) with γ = 0.5: choosing a higher decision threshold pushes the counterfactual a little further into the target domain; this effect is even stronger for ClaPROAR; finally, using the Gravitational generator the counterfactual ends up all the way inside the target domain. Find out more in the [paper](paper/paper.pdf).
 
 ![](paper/www/mitigation.png)
+
+## References

bib.bib

+@InProceedings{altmeyer2023endogenous,
+  author    = {Altmeyer, Patrick and Angela, Giovan and Buszydlik, Aleksander and Dobiczek, Karol and van Deursen, Arie and Liem, Cynthia},
+  booktitle = {First {IEEE} {Conference} on {Secure} and {Trustworthy} {Machine} {Learning}},
+  date      = {2023},
+  title     = {Endogenous {Macrodynamics} in {Algorithmic} {Recourse}},
+  file      = {:altmeyerendogenous - Endogenous Macrodynamics in Algorithmic Recourse.pdf:PDF},
+}
+
 %% This BibTeX bibliography file was created using BibDesk.
 %% https://bibdesk.sourceforge.io/
 
@@ -2386,4 +2394,13 @@
   keywords    = {Computer Science - Machine Learning, Computer Science - Data Structures and Algorithms, Computer Science - Computer Science and Game Theory, Statistics - Machine Learning},
 }
 
+@Article{pawelczyk2022probabilistically,
+  author       = {Pawelczyk, Martin and Datta, Teresa and van-den-Heuvel, Johannes and Kasneci, Gjergji and Lakkaraju, Himabindu},
+  date         = {2022},
+  journaltitle = {arXiv preprint arXiv:2203.06768},
+  title        = {Probabilistically {Robust} {Recourse}: {Navigating} the {Trade}-offs between {Costs} and {Robustness} in {Algorithmic} {Recourse}},
+  file         = {:pawelczyk2022probabilistically - Probabilistically Robust Recourse_ Navigating the Trade Offs between Costs and Robustness in Algorithmic Recourse.pdf:PDF},
+  shorttitle   = {Probabilistically {Robust} {Recourse}},
+}
+
 @Comment{jabref-meta: databaseType:biblatex;}