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<!doctype html><html lang=en-uk><head><script data-goatcounter=https://ruivieira-dev.goatcounter.com/count async src=//gc.zgo.at/count.js></script><script src=https://unpkg.com/@alpinejs/intersect@3.x.x/dist/cdn.min.js></script><script src=https://unpkg.com/alpinejs@3.x.x/dist/cdn.min.js></script><script type=module src=https://ruivieira.dev/js/deeplinks/deeplinks.js></script><link rel=preload href=https://ruivieira.dev/lib/fonts/fa-brands-400.woff2 as=font type=font/woff2 crossorigin=anonymous><link rel=preload href=https://ruivieira.dev/lib/fonts/fa-regular-400.woff2 as=font type=font/woff2 crossorigin=anonymous><link rel=preload href=https://ruivieira.dev/lib/fonts/fa-solid-900.woff2 as=font type=font/woff2 crossorigin=anonymous><link rel=preload href=https://ruivieira.dev/fonts/firacode/FiraCode-Regular.woff2 as=font type=font/woff2 crossorigin=anonymous><link rel=preload href=https://ruivieira.dev/fonts/vollkorn/Vollkorn-Regular.woff2 as=font type=font/woff2 crossorigin=anonymous><link rel=stylesheet href=https://ruivieira.dev/css/kbd.css type=text/css><meta charset=utf-8><meta http-equiv=X-UA-Compatible content="IE=edge"><title>Explainability · Rui Vieira</title>
<link rel=canonical href=https://ruivieira.dev/explainability.html><meta name=viewport content="width=device-width,initial-scale=1"><meta name=robots content="all,follow"><meta name=googlebot content="index,follow,snippet,archive"><meta property="og:title" content="Explainability"><meta property="og:description" content="Topics Counterfactuals Counterfactuals with Constraint Solvers LIME and the deterministic version, DLIME Resources TrustyAI Explainability Toolkit1 pre-print, https://arxiv.org/abs/2104.12717 A nice presentation on AI/ML explainability: https://explainml-tutorial.github.io/neurips20 Software omnixai Literature Kakogeorgiou, Ioannis, and Konstantinos Karantzalos. “Evaluating Explainable Artificial Intelligence Methods for Multi-label Deep Learning Classification Tasks in Remote Sensing.” arXiv preprint arXiv:2104.01375 (2021). Geada, Rob, Tommaso Teofili, Rui Vieira, Rebecca Whitworth and Daniele Zonca. “TrustyAI Explainability Toolkit.” (2021). ↩︎"><meta property="og:type" content="article"><meta property="og:url" content="https://ruivieira.dev/explainability.html"><meta property="article:section" content="posts"><meta property="article:modified_time" content="2023-10-01T20:46:29+01:00"><meta name=twitter:card content="summary"><meta name=twitter:title content="Explainability"><meta name=twitter:description content="Topics Counterfactuals Counterfactuals with Constraint Solvers LIME and the deterministic version, DLIME Resources TrustyAI Explainability Toolkit1 pre-print, https://arxiv.org/abs/2104.12717 A nice presentation on AI/ML explainability: https://explainml-tutorial.github.io/neurips20 Software omnixai Literature Kakogeorgiou, Ioannis, and Konstantinos Karantzalos. “Evaluating Explainable Artificial Intelligence Methods for Multi-label Deep Learning Classification Tasks in Remote Sensing.” arXiv preprint arXiv:2104.01375 (2021). Geada, Rob, Tommaso Teofili, Rui Vieira, Rebecca Whitworth and Daniele Zonca. “TrustyAI Explainability Toolkit.” (2021). ↩︎"><link rel=stylesheet href=https://ruivieira.dev/css/styles.css><!--[if lt IE 9]><script src=https://oss.maxcdn.com/html5shiv/3.7.2/html5shiv.min.js></script><script src=https://oss.maxcdn.com/respond/1.4.2/respond.min.js></script><![endif]--><link rel=icon type=image/png href=https://ruivieira.dev/images/favicon.ico></head><body class="max-width mx-auto px3 ltr" x-data="{currentHeading: undefined}"><div class="content index py4"><div id=header-post><a id=menu-icon href=#><i class="fas fa-eye fa-lg"></i></a>
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<a href=https://ruivieira.dev/counterfactuals.html>Counterfactuals</a></li></ul></nav></div></span></div><article class=post itemscope itemtype=http://schema.org/BlogPosting><header><h1 class=posttitle itemprop="name headline">Explainability</h1><div class=meta><div class=postdate>Updated <time datetime="2023-10-01 20:46:29 +0100 BST" itemprop=datePublished>2023-10-01</time>
<span class=commit-hash>(<a href=https://ruivieira.dev/log/index.html#e23fe25>e23fe25</a>)</span></div></div></header><div class=content itemprop=articleBody><h2 id=topics x-intersect="currentHeading = '#topics'">Topics</h2><ul><li><a href=https://ruivieira.dev/counterfactuals.html>Counterfactuals</a><ul><li><a href=https://ruivieira.dev/counterfactuals-with-constraint-solvers.html>Counterfactuals with Constraint Solvers</a></li></ul></li><li>LIME and the deterministic version, <a href=https://ruivieira.dev/dlime.html>DLIME</a></li></ul><h2 id=resources x-intersect="currentHeading = '#resources'">Resources</h2><ul><li>TrustyAI Explainability Toolkit<sup id=fnref:1><a href=#fn:1 class=footnote-ref role=doc-noteref>1</a></sup> pre-print, <a href=https://arxiv.org/abs/2104.12717>https://arxiv.org/abs/2104.12717</a></li><li>A nice presentation on AI/ML explainability: <a href=https://explainml-tutorial.github.io/neurips20>https://explainml-tutorial.github.io/neurips20</a></li></ul><h3 id=software x-intersect="currentHeading = '#software'">Software</h3><ul><li><a href=https://blog.salesforceairesearch.com/omnixai/>omnixai</a></li></ul><h2 id=literature x-intersect="currentHeading = '#literature'">Literature</h2><ul><li>Kakogeorgiou, Ioannis, and Konstantinos Karantzalos. “<em>Evaluating Explainable Artificial Intelligence Methods for Multi-label Deep Learning Classification Tasks in Remote Sensing.</em>” <em>arXiv preprint <a href=https://arxiv.org/abs/2104.01375>arXiv:2104.01375</a></em> (2021).</li></ul><div class=footnotes role=doc-endnotes><hr><ol><li id=fn:1><p>Geada, Rob, Tommaso Teofili, Rui Vieira, Rebecca Whitworth and Daniele Zonca. “TrustyAI Explainability Toolkit.” (2021). <a href=#fnref:1 class=footnote-backref role=doc-backlink>↩︎</a></p></li></ol></div></div></article><div id=footer-post-container><div id=footer-post><div id=nav-footer style=display:none><ul><li><a href=https://ruivieira.dev/>Home</a></li><li><a href=https://ruivieira.dev/blog/>Blog</a></li><li><a href=https://ruivieira.dev/draw/>Drawings</a></li><li><a href=https://ruivieira.dev/map/>All pages</a></li><li><a href=https://ruivieira.dev/search.html>Search</a></li></ul></div><div id=toc-footer style=display:none><nav id=TableOfContents><ul><li><a href=#topics>Topics</a></li><li><a href=#resources>Resources</a><ul><li><a href=#software>Software</a></li></ul></li><li><a href=#literature>Literature</a></li></ul></nav></div><div id=share-footer style=display:none></div><div id=actions-footer><a id=menu-toggle class=icon href=# onclick='return $("#nav-footer").toggle(),!1' aria-label=Menu><i class="fas fa-bars fa-lg" aria-hidden=true></i> Menu</a>
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