Robust Counterfactual Explanations for Neural Networks With
Probabilistic Guarantees

Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees

19 May 2023

Saumitra Mishra

Daniele Magazzeni

Sanghamitra Dutta

Papers citing "Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees"

11 / 11 papers shown

Title
From Search To Sampling: Generative Models For Robust Algorithmic Recourse Prateek Garg Lokesh Nagalapatti Sunita Sarawagi 31 0 0 12 May 2025
The Curious Case of Arbitrariness in Machine Learning Prakhar Ganesh Afaf Taik G. Farnadi 59 2 0 28 Jan 2025
S-CFE: Simple Counterfactual Explanations Shpresim Sadiku Moritz Wagner Sai Ganesh Nagarajan S. Pokutta 26 0 0 21 Oct 2024
Time Can Invalidate Algorithmic Recourse Giovanni De Toni Stefano Teso Bruno Lepri Andrea Passerini 37 0 0 10 Oct 2024
Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space Yukai Zhang Ao Xu Zihao Li Tieru Wu 42 1 0 31 May 2024
Even-Ifs From If-Onlys: Are the Best Semi-Factual Explanations Found Using Counterfactuals As Guides? Saugat Aryal Mark T. Keane 32 4 0 01 Mar 2024
Trust Regions for Explanations via Black-Box Probabilistic Certification Amit Dhurandhar Swagatam Haldar Dennis L. Wei K. Ramamurthy FAtt 21 2 0 17 Feb 2024
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
Consistent Counterfactuals for Deep Models Emily Black Zifan Wang Matt Fredrikson Anupam Datta BDL OffRL OOD 46 43 0 06 Oct 2021
BRPO: Batch Residual Policy Optimization Kentaro Kanamori Yinlam Chow Takuya Takagi Hiroki Arimura Honglak Lee Ken Kobayashi Craig Boutilier OffRL 136 46 0 08 Feb 2020
Issues with post-hoc counterfactual explanations: a discussion Thibault Laugel Marie-Jeanne Lesot Christophe Marsala Marcin Detyniecki CML 104 44 0 11 Jun 2019