Generative Counterfactuals for Neural Networks via Attribute-Informed
Perturbation

Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation

18 January 2021

Fan Yang

Ninghao Liu

Papers citing "Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation"

9 / 9 papers shown

Title
A General Search-based Framework for Generating Textual Counterfactual Explanations Daniel Gilo Shaul Markovitch LRM 44 0 0 01 Nov 2022
Differentially Private Counterfactuals via Functional Mechanism Fan Yang Qizhang Feng Kaixiong Zhou Jiahao Chen Xia Hu 32 8 0 04 Aug 2022
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space Eric Yeh Pedro Sequeira Jesse Hostetler Melinda Gervasio OOD CML BDL OffRL 25 2 0 15 Jul 2022
Counterfactual Explanations for Models of Code Jürgen Cito Işıl Dillig V. Murali S. Chandra AAML LRM 32 48 0 10 Nov 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 37 55 0 18 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 29 146 0 26 Feb 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
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,698 0 28 Feb 2017
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 312 13,377 0 25 Aug 2014