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Feature relevance quantification in explainable AI: A causal problem

29 October 2019

Papers citing "Feature relevance quantification in explainable AI: A causal problem"

21 / 21 papers shown

Title
Computing Exact Shapley Values in Polynomial Time for Product-Kernel Methods Majid Mohammadi Siu Lun Chau Krikamol Muandet FAtt 189 0 0 22 May 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 130 16 0 10 Jan 2025
Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory Fabian Fumagalli Maximilian Muschalik Eyke Hüllermeier Barbara Hammer J. Herbinger FAtt 189 4 0 22 Dec 2024
Unlearning-based Neural Interpretations Ching Lam Choi Alexandre Duplessis Serge Belongie FAtt 233 0 0 10 Oct 2024
Provably Accurate Shapley Value Estimation via Leverage Score Sampling Christopher Musco R. Teal Witter FAtt FedML TDI 88 5 0 02 Oct 2024
On the Tractability of SHAP Explanations Guy Van den Broeck A. Lykov Maximilian Schleich Dan Suciu FAtt TDI 66 276 0 18 Sep 2020
Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach A. Moawad E. Islam Namdoo Kim R. Vijayagopal A. Rousseau Wei Biao Wu 63 5 0 15 Jun 2020
The many Shapley values for model explanation Mukund Sundararajan A. Najmi TDI FAtt 62 635 0 22 Aug 2019
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values K. Aas Martin Jullum Anders Løland FAtt TDI 65 624 0 25 Mar 2019
Neural Network Attributions: A Causal Perspective Aditya Chattopadhyay Piyushi Manupriya Anirban Sarkar V. Balasubramanian CML 55 146 0 06 Feb 2019
Consistent Individualized Feature Attribution for Tree Ensembles Scott M. Lundberg G. Erion Su-In Lee FAtt TDI 66 1,405 0 12 Feb 2018
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 88 1,097 0 27 Dec 2017
Avoiding Discrimination through Causal Reasoning Niki Kilbertus Mateo Rojas-Carulla Giambattista Parascandolo Moritz Hardt Dominik Janzing Bernhard Schölkopf FaML CML 115 584 0 08 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,002 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,881 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,018 0 04 Mar 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 545 5,909 0 08 Jul 2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 85 791 0 05 May 2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller Wojciech Samek FAtt 77 462 0 04 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,027 0 16 Feb 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,121 0 20 Dec 2014