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[deps]
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title: |
`Documenter.jl`
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bib.bib 0 → 100644
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<!DOCTYPE html>
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<title>Research Proposal</title>
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<h2 id="toc-title">Table of contents</h2>
<ul>
<li><a href="#you-may-not-like-it-but-this-is-what-counterfactuals-look-like" id="toc-you-may-not-like-it-but-this-is-what-counterfactuals-look-like" class="nav-link active" data-scroll-target="#you-may-not-like-it-but-this-is-what-counterfactuals-look-like">You may not like it, but this is what counterfactuals look like</a></li>
<li><a href="#introduction-to-conformal-prediction" id="toc-introduction-to-conformal-prediction" class="nav-link" data-scroll-target="#introduction-to-conformal-prediction">Introduction to Conformal Prediction</a>
<ul class="collapse">
<li><a href="#post-hoc" id="toc-post-hoc" class="nav-link" data-scroll-target="#post-hoc">Post-hoc</a></li>
<li><a href="#intrinsic-conformal-training-maybe" id="toc-intrinsic-conformal-training-maybe" class="nav-link" data-scroll-target="#intrinsic-conformal-training-maybe">Intrinsic — Conformal Training [MAYBE]</a></li>
</ul></li>
<li><a href="#conformal-counterfactuals" id="toc-conformal-counterfactuals" class="nav-link" data-scroll-target="#conformal-counterfactuals">Conformal Counterfactuals</a>
<ul class="collapse">
<li><a href="#research-questions" id="toc-research-questions" class="nav-link" data-scroll-target="#research-questions">Research Questions</a></li>
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<li><a href="#experiments" id="toc-experiments" class="nav-link" data-scroll-target="#experiments">Experiments</a></li>
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<h1 class="title">Research Proposal</h1>
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</div>
</header>
<section id="you-may-not-like-it-but-this-is-what-counterfactuals-look-like" class="level2">
<h2 class="anchored" data-anchor-id="you-may-not-like-it-but-this-is-what-counterfactuals-look-like">You may not like it, but this is what counterfactuals look like</h2>
<ul>
<li>Show DiCE for weak MLP</li>
<li>Show Latent for same weak MLP</li>
<li>Latent can be manipulated:
<ul>
<li>train biased model</li>
<li>train VAE with biased variable removed/attacked (use Boston housing dataset)</li>
<li>hypothesis: will generate bias-free explanations</li>
</ul></li>
</ul>
</section>
<section id="introduction-to-conformal-prediction" class="level2">
<h2 class="anchored" data-anchor-id="introduction-to-conformal-prediction">Introduction to Conformal Prediction</h2>
<ul>
<li>distribution-free, model-agnostic and scalable approach to predictive uncertainty quantification</li>
</ul>
<section id="post-hoc" class="level3">
<h3 class="anchored" data-anchor-id="post-hoc">Post-hoc</h3>
<ul>
<li>Take any fitted model and turn it into a conformal model using calibration data.</li>
</ul>
</section>
<section id="intrinsic-conformal-training-maybe" class="level3">
<h3 class="anchored" data-anchor-id="intrinsic-conformal-training-maybe">Intrinsic — Conformal Training [MAYBE]</h3>
<ul>
<li>Model explicitly trained for conformal prediction.</li>
</ul>
</section>
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<section id="conformal-counterfactuals" class="level2">
<h2 class="anchored" data-anchor-id="conformal-counterfactuals">Conformal Counterfactuals</h2>
<ul>
<li>Realistic counterfactuals by minimizing predictive uncertainty <span class="citation" data-cites="schut2021generating">(<a href="#ref-schut2021generating" role="doc-biblioref">Schut et al. 2021</a>)</span>.</li>
<li>Problem: restricted to Bayesian models.</li>
<li>Solution: post-hoc predictive uncertainty quantification.</li>
<li>Conformal prediction is instance-based. So is CE.</li>
<li>Does the coverage guarantee carry over to counterfactuals?</li>
</ul>
<section id="research-questions" class="level3">
<h3 class="anchored" data-anchor-id="research-questions">Research Questions</h3>
<ul>
<li>Is CP alone enough to ensure realistic counterfactuals?</li>
<li>Do counterfactuals improve further as the models get better?</li>
<li>Do counterfactuals get more realistic as coverage</li>
<li>What happens as we vary coverage and setsize?</li>
<li>What happens as we improve the model robustness?</li>
<li>What happens as we improve the model’s ability to incorporate predictive uncertainty (deep ensemble, laplace)?</li>
</ul>
</section>
</section>
<section id="experiments" class="level2">
<h2 class="anchored" data-anchor-id="experiments">Experiments</h2>
<ul>
<li>Maybe: conformalised Laplace</li>
<li>Benchmarking:
<ul>
<li>add PROBE into the mix</li>
<li>compare travel costs to domain shits.</li>
</ul></li>
</ul>
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<section id="references" class="level2 unnumbered">
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<div id="quarto-appendix" class="default"><section class="quarto-appendix-contents" role="doc-bibliography"><h2 class="anchored quarto-appendix-heading">References</h2><div id="refs" class="references csl-bib-body hanging-indent" role="doc-bibliography">
<div id="ref-schut2021generating" class="csl-entry" role="doc-biblioentry">
Schut, Lisa, Oscar Key, Rory Mc Grath, Luca Costabello, Bogdan Sacaleanu, Yarin Gal, et al. 2021. <span>“Generating <span>Interpretable Counterfactual Explanations By Implicit Minimisation</span> of <span>Epistemic</span> and <span>Aleatoric Uncertainties</span>.”</span> In <em>International <span>Conference</span> on <span>Artificial Intelligence</span> and <span>Statistics</span></em>, 1756–64. <span>PMLR</span>.
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// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
//
// AnchorJS - v4.3.1 - 2021-04-17
// https://www.bryanbraun.com/anchorjs/
// Copyright (c) 2021 Bryan Braun; Licensed MIT
//
// @license magnet:?xt=urn:btih:d3d9a9a6595521f9666a5e94cc830dab83b65699&dn=expat.txt Expat
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// @license-end
\ No newline at end of file
/**
* @popperjs/core v2.11.4 - MIT License
*/
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This diff is collapsed.
This diff is collapsed.
.tippy-box[data-animation=fade][data-state=hidden]{opacity:0}[data-tippy-root]{max-width:calc(100vw - 10px)}.tippy-box{position:relative;background-color:#333;color:#fff;border-radius:4px;font-size:14px;line-height:1.4;white-space:normal;outline:0;transition-property:transform,visibility,opacity}.tippy-box[data-placement^=top]>.tippy-arrow{bottom:0}.tippy-box[data-placement^=top]>.tippy-arrow:before{bottom:-7px;left:0;border-width:8px 8px 0;border-top-color:initial;transform-origin:center top}.tippy-box[data-placement^=bottom]>.tippy-arrow{top:0}.tippy-box[data-placement^=bottom]>.tippy-arrow:before{top:-7px;left:0;border-width:0 8px 8px;border-bottom-color:initial;transform-origin:center bottom}.tippy-box[data-placement^=left]>.tippy-arrow{right:0}.tippy-box[data-placement^=left]>.tippy-arrow:before{border-width:8px 0 8px 8px;border-left-color:initial;right:-7px;transform-origin:center left}.tippy-box[data-placement^=right]>.tippy-arrow{left:0}.tippy-box[data-placement^=right]>.tippy-arrow:before{left:-7px;border-width:8px 8px 8px 0;border-right-color:initial;transform-origin:center right}.tippy-box[data-inertia][data-state=visible]{transition-timing-function:cubic-bezier(.54,1.5,.38,1.11)}.tippy-arrow{width:16px;height:16px;color:#333}.tippy-arrow:before{content:"";position:absolute;border-color:transparent;border-style:solid}.tippy-content{position:relative;padding:5px 9px;z-index:1}
\ No newline at end of file
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