An Interpretable Probabilistic Approach for Demystifying Black-box
Predictive Models

An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models

21 July 2020

Catarina Moreira

Renuka Sindhgatta

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Papers citing "An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models"

14 / 14 papers shown

Title
A Tutorial on Learning With Bayesian Networks David Heckerman CML 451 3,518 0 01 Feb 2020
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 133 725 0 08 Jan 2020
"Why Should You Trust My Explanation?" Understanding Uncertainty in LIME Explanations Hui Fen Tan Kuangyan Song Yiming Sun Yujia Zhang Madeilene Udell FAtt 115 19 0 29 Apr 2019
Interpretable machine learning: definitions, methods, and applications W. James Murdoch Chandan Singh Karl Kumbier R. Abbasi-Asl Bin Yu XAI HAI 201 1,445 0 14 Jan 2019
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 53 99 0 22 Apr 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 150 3,989 0 06 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 138 2,371 0 01 Nov 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 413 3,820 0 28 Feb 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,716 0 10 Jun 2016
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 306 729 0 12 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 121 3,984 0 27 Feb 2013
Counterfactual Reasoning and Learning Systems Léon Bottou J. Peters J. Q. Candela Denis Xavier Charles D. M. Chickering Elon Portugaly Dipankar Ray Patrice Y. Simard Edward Snelson CML OffRL 402 787 0 11 Sep 2012

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