v1v2 (latest)

A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability

5 May 2025

Pouria Fatemi

Ehsan Sharifian

Mohammad Hossein Yassaee

ArXiv (abs)PDF HTML

Papers citing "A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability"

23 / 23 papers shown

Title
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 70 6 0 11 Oct 2023
Counterfactual Identifiability of Bijective Causal Models Arash Nasr-Esfahany MohammadIman Alizadeh Devavrat Shah CML BDL 94 27 0 04 Feb 2023
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 78 14 0 13 Dec 2022
Curious Exploration via Structured World Models Yields Zero-Shot Object Manipulation Cansu Sancaktar Sebastian Blaes Georg Martius LM&Ro 51 26 0 22 Jun 2022
On the Adversarial Robustness of Causal Algorithmic Recourse Ricardo Dominguez-Olmedo Amir-Hossein Karimi Bernhard Schölkopf 75 63 0 21 Dec 2021
Counterfactual Explanations Can Be Manipulated Dylan Slack Sophie Hilgard Himabindu Lakkaraju Sameer Singh 71 137 0 04 Jun 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 135 70 0 02 Mar 2021
Causal Shapley Values: Exploiting Causal Knowledge to Explain Individual Predictions of Complex Models Tom Heskes E. Sijben I. G. Bucur Tom Claassen FAtt TDI 109 154 0 03 Nov 2020
Shapley Flow: A Graph-based Approach to Interpreting Model Predictions Jiaxuan Wang Jenna Wiens Scott M. Lundberg FAtt 95 90 0 27 Oct 2020
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 116 85 0 13 Oct 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 104 181 0 11 Jun 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 59 341 0 14 Feb 2020
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability Christopher Frye C. Rowat Ilya Feige 70 183 0 14 Oct 2019
FACE: Feasible and Actionable Counterfactual Explanations Rafael Poyiadzi Kacper Sokol Raúl Santos-Rodríguez T. D. Bie Peter A. Flach 73 369 0 20 Sep 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 91 322 0 27 May 2019
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 124 591 0 21 Feb 2018
Inverse Classification for Comparison-based Interpretability in Machine Learning Thibault Laugel Marie-Jeanne Lesot Christophe Marsala X. Renard Marcin Detyniecki 123 101 0 22 Dec 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 127 2,361 0 01 Nov 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 22,002 0 22 May 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,813 0 28 Feb 2017
"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
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 282 14,961 1 21 Dec 2013