Explaining Deep Learning Models with Constrained Adversarial Examples

25 June 2019

Papers citing "Explaining Deep Learning Models with Constrained Adversarial Examples"

8 / 8 papers shown

Title
Model-Free Counterfactual Subset Selection at Scale Minh Nguyen Viet Hung Doan Anh Tuan Nguyen Jun Jo Quoc Viet Hung Nguyen LRM 57 0 0 12 Feb 2025
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
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 40 33 0 09 Jul 2021
Causal Learning for Socially Responsible AI Lu Cheng Ahmadreza Mosallanezhad Paras Sheth Huan Liu 85 13 0 25 Apr 2021
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 46 62 0 11 Sep 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 29 213 0 09 Mar 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 353 5,849 0 08 Jul 2016