Explaining Deep Learning Models using Causal Inference

11 November 2018

Papers citing "Explaining Deep Learning Models using Causal Inference"

27 / 27 papers shown

Title
ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering Paritosh Parmar Eric Peh Basura Fernando VGen LRM 60 0 0 28 Aug 2025
Causality-Driven Neural Network Repair: Challenges and Opportunities Fatemeh Vares Brittany Johnson AAML 157 1 0 24 Apr 2025
CausAdv: A Causal-based Framework for Detecting Adversarial Examples Hichem Debbi CML AAML 169 1 0 29 Oct 2024
Investigating and unmasking feature-level vulnerabilities of CNNs to adversarial perturbations Davide Coppola Hwee Kuan Lee AAML 147 1 0 31 May 2024
Causality Analysis for Evaluating the Security of Large Language Models Wei Zhao Zhe Li Junfeng Sun 147 14 0 13 Dec 2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 231 5 0 01 Mar 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 258 15 0 07 Nov 2022
Causality-based Neural Network RepairInternational Conference on Software Engineering (ICSE), 2022 Bing-Jie Sun Jun Sun Hong Long Pham Jie Shi 109 97 0 20 Apr 2022
Evaluation Methods and Measures for Causal Learning AlgorithmsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 204 69 0 07 Feb 2022
On Causal Inference for Data-free Structured Pruning Martin Ferianc A. Sankaran Olivier Mastropietro Ehsan Saboori Quentin Cappart CML 79 2 0 19 Dec 2021
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model ExplanationAAAI Conference on Artificial Intelligence (AAAI), 2021 Thien Q. Tran Kazuto Fukuchi Youhei Akimoto Jun Sakuma CML 177 10 0 09 Sep 2021
Causal Learning for Socially Responsible AIInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Lu Cheng Ahmadreza Mosallanezhad Paras Sheth Huan Liu 248 14 0 25 Apr 2021
Generative Causal Explanations for Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Wanyu Lin Hao Lan Baochun Li CML 166 203 0 14 Apr 2021
Explainability of deep vision-based autonomous driving systems: Review and challengesInternational Journal of Computer Vision (IJCV), 2021 Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 400 203 0 13 Jan 2021
Socially Responsible AI Algorithms: Issues, Purposes, and ChallengesJournal of Artificial Intelligence Research (JAIR), 2021 Lu Cheng Kush R. Varshney Huan Liu FaML 383 182 0 01 Jan 2021
Examining the causal structures of deep neural networks using information theory Simon Mattsson Eric J. Michaud Erik P. Hoel 122 10 0 26 Oct 2020
Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design Shusen Liu B. Kailkhura Jize Zhang A. Hiszpanski Emily Robertson Donald Loveland T. Y. Han 98 2 0 16 Jul 2020
Actionable Attribution Maps for Scientific Machine Learning Shusen Liu B. Kailkhura Jize Zhang A. Hiszpanski Emily Robertson Donald Loveland T. Y. Han 79 1 0 30 Jun 2020
Causal Explanations of Image Misclassifications Yan Min Miles K. Bennett CML 80 1 0 28 Jun 2020
Causality Learning: A New Perspective for Interpretable Machine Learning Guandong Xu Tri Dung Duong Cunliang Kong S. Liu Xianzhi Wang XAI OOD CML 170 61 0 27 Jun 2020
Generative causal explanations of black-box classifiersNeural Information Processing Systems (NeurIPS), 2020 Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 213 76 0 24 Jun 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Helen Zhou AAML 154 8 0 23 Apr 2020
Causal Interpretability for Machine Learning -- Problems, Methods and EvaluationSIGKDD Explorations (SIGKDD Explor.), 2020 Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 228 240 0 09 Mar 2020
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Helen Zhou XAI ELM 145 76 0 16 Jul 2019
Generative Counterfactual Introspection for Explainable Deep LearningIEEE Global Conference on Signal and Information Processing (GlobalSIP), 2019 Shusen Liu B. Kailkhura Donald Loveland Yong Han 203 94 0 06 Jul 2019
HARK Side of Deep Learning -- From Grad Student Descent to Automated Machine Learning O. Gencoglu M. Gils E. Guldogan Chamin Morikawa Mehmet Süzen M. Gruber J. Leinonen H. Huttunen 141 38 0 16 Apr 2019
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural NetworksInternational Conference on Information Photonics (ICIP), 2019 Chao-Han Huck Yang Yi-Chieh Liu Pin-Yu Chen Xiaoli Ma Y. Tsai BDL AAML CML 169 21 0 09 Feb 2019