Counterfactual Explanations for Machine Learning: Challenges Revisited

Counterfactual Explanations for Machine Learning: Challenges Revisited

14 June 2021

John P Dickerson

Keegan E. Hines

Papers citing "Counterfactual Explanations for Machine Learning: Challenges Revisited"

14 / 14 papers shown

Title
Beyond One-Size-Fits-All: Adapting Counterfactual Explanations to User Objectives Orfeas Menis Mastromichalakis Jason Liartis Giorgos Stamou 24 1 0 12 Apr 2024
View-based Explanations for Graph Neural Networks Tingyang Chen Dazhuo Qiu Yinghui Wu Arijit Khan Xiangyu Ke Yunjun Gao 46 9 0 04 Jan 2024
Survey on AI Ethics: A Socio-technical Perspective Dave Mbiazi Meghana Bhange Maryam Babaei Ivaxi Sheth Patrik Kenfack 23 4 0 28 Nov 2023
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems Yiming Li Daling Wang Wenfang Wu Shi Feng Yifei Zhang CML 50 1 0 28 Sep 2023
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks Lorenz Linhardt Klaus-Robert Muller G. Montavon AAML 31 7 0 12 Apr 2023
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning Jasmina Gajcin Ivana Dusparic CML 32 3 0 08 Mar 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 44 3 0 07 Feb 2023
Evaluating counterfactual explanations using Pearl's counterfactual method Bevan I. Smith CML 30 1 0 06 Jan 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 35 16 0 16 Dec 2022
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities Jasmina Gajcin Ivana Dusparic CML OffRL 37 8 0 21 Oct 2022
Interpretation of Black Box NLP Models: A Survey Shivani Choudhary N. Chatterjee S. K. Saha FAtt 34 10 0 31 Mar 2022
MCCE: Monte Carlo sampling of realistic counterfactual explanations Annabelle Redelmeier Martin Jullum K. Aas Anders Løland BDL 37 11 0 18 Nov 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 26 164 0 20 Oct 2020
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 195 742 0 13 Dec 2018