On Computing Probabilistic Abductive Explanations

12 December 2022

Papers citing "On Computing Probabilistic Abductive Explanations"

38 / 38 papers shown

Title
A Fast Kernel-based Conditional Independence test with Application to Causal Discovery Oliver Schacht Biwei Huang 195 0 0 16 May 2025
On Computing Relevant Features for Explaining NBCs Yacine Izza Sasha Rubin 84 5 0 11 Jul 2022
On Computing Probabilistic Explanations for Decision Trees Marcelo Arenas Pablo Barceló M. Romero Bernardo Subercaseaux FAtt 73 42 0 30 Jun 2022
ASTERYX : A model-Agnostic SaT-basEd appRoach for sYmbolic and score-based eXplanations Ryma Boumazouza Fahima Cheikh Bertrand Mazure Karim Tabia 47 32 0 23 Jun 2022
Eliminating The Impossible, Whatever Remains Must Be True Jinqiang Yu Alexey Ignatiev Peter Stuckey Nina Narodytska Sasha Rubin 69 23 0 20 Jun 2022
On Tackling Explanation Redundancy in Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 75 64 0 20 May 2022
Provably Precise, Succinct and Efficient Explanations for Decision Trees Yacine Izza Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt 73 8 0 19 May 2022
On Deciding Feature Membership in Explanations of SDD & Related Classifiers Xuanxiang Huang Sasha Rubin FAtt LRM 45 3 0 15 Feb 2022
On Efficiently Explaining Graph-Based Classifiers Xuanxiang Huang Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 78 39 0 02 Jun 2021
Efficient Explanations With Relevant Sets Yacine Izza Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt 72 16 0 01 Jun 2021
Explanations for Monotonic Classifiers Sasha Rubin Thomas Gerspacher M. Cooper Alexey Ignatiev Nina Narodytska FAtt 76 46 0 01 Jun 2021
On Explaining Random Forests with SAT Yacine Izza Sasha Rubin FAtt 105 75 0 21 May 2021
Probabilistic Sufficient Explanations Eric Wang Pasha Khosravi Guy Van den Broeck XAI FAtt TPM 154 25 0 21 May 2021
SAT-Based Rigorous Explanations for Decision Lists Alexey Ignatiev Sasha Rubin XAI 61 46 0 14 May 2021
On Guaranteed Optimal Robust Explanations for NLP Models Emanuele La Malfa A. Zbrzezny Rhiannon Michelmore Nicola Paoletti Marta Z. Kwiatkowska FAtt 59 48 0 08 May 2021
On the Computational Intelligibility of Boolean Classifiers Gilles Audemard S. Bellart Louenas Bounia F. Koriche Jean-Marie Lagniez Pierre Marquis 45 58 0 13 Apr 2021
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 79 88 0 21 Oct 2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay Sasha Rubin Thomas Gerspacher Martin C. Cooper Alexey Ignatiev Nina Narodytska FAtt 58 63 0 13 Aug 2020
On The Reasons Behind Decisions Adnan Darwiche Auguste Hirth FaML 54 149 0 21 Feb 2020
A Formal Approach to Explainability Lior Wolf Tomer Galanti Tamir Hazan FAtt GAN 56 22 0 15 Jan 2020
When Explanations Lie: Why Many Modified BP Attributions Fail Leon Sixt Maximilian Granz Tim Landgraf BDL FAtt XAI 58 132 0 20 Dec 2019
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 68 255 0 15 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 79 821 0 06 Nov 2019
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods Oana-Maria Camburu Eleonora Giunchiglia Jakob N. Foerster Thomas Lukasiewicz Phil Blunsom FAtt AAML 74 61 0 04 Oct 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 75 443 0 26 Sep 2019
How to Manipulate CNNs to Make Them Lie: the GradCAM Case T. Viering Ziqi Wang Marco Loog E. Eisemann AAML FAtt 39 28 0 25 Jul 2019
Abduction-Based Explanations for Machine Learning Models Alexey Ignatiev Nina Narodytska Sasha Rubin FAtt 57 226 0 26 Nov 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 148 1,969 0 08 Oct 2018
A Symbolic Approach to Explaining Bayesian Network Classifiers Andy Shih Arthur Choi Adnan Darwiche FAtt 74 243 0 09 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 143 3,970 0 06 Feb 2018
The (Un)reliability of saliency methods Pieter-Jan Kindermans Sara Hooker Julius Adebayo Maximilian Alber Kristof T. Schütt Sven Dähne D. Erhan Been Kim FAtt XAI 106 688 0 02 Nov 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 293 2,267 0 24 Jun 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 250 4,273 0 22 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,018 0 22 May 2017
PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison Randal S. Olson William La Cava Patryk Orzechowski Ryan J. Urbanowicz J. Moore 407 380 0 01 Mar 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,033 0 16 Feb 2016
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 314 7,316 0 20 Dec 2013
A Knowledge Compilation Map Adnan Darwiche Pierre Marquis 96 953 0 09 Jun 2011