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Axiomatic Attribution for Deep Networks

4 March 2017

Ankur Taly

Papers citing "Axiomatic Attribution for Deep Networks"

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Title
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations Sushant Agarwal S. Jabbari Chirag Agarwal Sohini Upadhyay Zhiwei Steven Wu Himabindu Lakkaraju FAtt AAML 93 64 0 21 Feb 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays Joseph Paul Cohen Rupert Brooks Sovann En Evan Zucker Anuj Pareek M. Lungren Akshay S. Chaudhari FAtt MedIm 85 4 0 18 Feb 2021
Unified Shapley Framework to Explain Prediction Drift Aalok Shanbhag A. Ghosh Josh Rubin FAtt FedML AI4TS 72 3 0 15 Feb 2021
Integrated Grad-CAM: Sensitivity-Aware Visual Explanation of Deep Convolutional Networks via Integrated Gradient-Based Scoring S. Sattarzadeh M. Sudhakar Konstantinos N. Plataniotis Jongseong Jang Yeonjeong Jeong Hyunwoo J. Kim FAtt 59 39 0 15 Feb 2021
Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks M. Sudhakar S. Sattarzadeh Konstantinos N. Plataniotis Jongseong Jang Yeonjeong Jeong Hyunwoo J. Kim AAML 65 11 0 15 Feb 2021
Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs Jaehwan Lee Joon‐Hyuk Chang TDI FAtt 98 0 0 15 Feb 2021
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset Chuizheng Meng Loc Trinh Nan Xu Yan Liu 67 30 0 12 Feb 2021
SCOUT: Socially-COnsistent and UndersTandable Graph Attention Network for Trajectory Prediction of Vehicles and VRUs Sandra Carrasco David Fernández Llorca Miguel Ángel Sotelo 56 53 0 12 Feb 2021
What does LIME really see in images? Damien Garreau Dina Mardaoui FAtt 64 40 0 11 Feb 2021
Inductive Granger Causal Modeling for Multivariate Time Series Yunfei Chu Xiaowei Wang Jianxin Ma Kunyang Jia Jingren Zhou Hongxia Yang CML AI4TS 63 11 0 10 Feb 2021
WheaCha: A Method for Explaining the Predictions of Models of Code Yu Wang Ke Wang Linzhang Wang FAtt 52 3 0 09 Feb 2021
RECAST: Enabling User Recourse and Interpretability of Toxicity Detection Models with Interactive Visualization Austin P. Wright Omar Shaikh Haekyu Park Will Epperson Muhammed Ahmed Stephane Pinel Duen Horng Chau Diyi Yang 44 22 0 08 Feb 2021
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders Harshana Habaragamuwa Y. Oishi Kenichi Tanaka 106 9 0 05 Feb 2021
HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks Yuanyuan Chen Boyang Albert Li Han Yu Pengcheng Wu Chunyan Miao TDI 106 42 0 04 Feb 2021
IWA: Integrated Gradient based White-box Attacks for Fooling Deep Neural Networks Yixiang Wang Jiqiang Liu Xiaolin Chang J. Misic Vojislav B. Mišić AAML 69 12 0 03 Feb 2021
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation R. Yamashita J. Long Snikitha Banda Jeanne Shen D. Rubin OOD MedIm 70 51 0 02 Feb 2021
Counterfactual Generation with Knockoffs Oana-Iuliana Popescu M. Shadaydeh Joachim Denzler 42 6 0 01 Feb 2021
Hierarchical Variational Autoencoder for Visual Counterfactuals Nicolas Vercheval A. Pižurica CML DRL BDL 87 2 0 01 Feb 2021
Counterfactual State Explanations for Reinforcement Learning Agents via Generative Deep Learning Matthew Lyle Olson Roli Khanna Lawrence Neal Fuxin Li Weng-Keen Wong CML 92 75 0 29 Jan 2021
Explaining Natural Language Processing Classifiers with Occlusion and Language Modeling David Harbecke AAML 53 2 0 28 Jan 2021
Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison Lukas Brunke Prateek Agrawal Nikhil George AAML FAtt 59 13 0 26 Jan 2021
Show or Suppress? Managing Input Uncertainty in Machine Learning Model Explanations Danding Wang Wencan Zhang Brian Y. Lim FAtt 56 22 0 23 Jan 2021
i-Algebra: Towards Interactive Interpretability of Deep Neural Networks Xinyang Zhang Ren Pang S. Ji Fenglong Ma Ting Wang HAI AI4CE 38 5 0 22 Jan 2021
Benchmarking Perturbation-based Saliency Maps for Explaining Atari Agents Tobias Huber Benedikt Limmer Elisabeth André FAtt 39 14 0 18 Jan 2021
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation Fan Yang Ninghao Liu Mengnan Du X. Hu OOD 53 17 0 18 Jan 2021
Generating Attribution Maps with Disentangled Masked Backpropagation Adria Ruiz Antonio Agudo Francesc Moreno FAtt 40 1 0 17 Jan 2021
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning Xiaoyang Sean Wang Yue Liu Yibo Jacky Zhang B. Kailkhura Klara Nahrstedt 26 3 0 15 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 186 178 0 13 Jan 2021
Convolutional Neural Nets in Chemical Engineering: Foundations, Computations, and Applications Shengli Jiang Victor M. Zavala AI4CE 36 28 0 13 Jan 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 152 105 0 11 Jan 2021
SyReNN: A Tool for Analyzing Deep Neural Networks Matthew Sotoudeh Aditya V. Thakur AAML GNN 63 16 0 09 Jan 2021
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information Zhengqi He Taro Toyoizumi 54 1 0 08 Jan 2021
Who's a Good Boy? Reinforcing Canine Behavior in Real-Time using Machine Learning Jason Stock Tom Cavey 20 2 0 07 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Mohamed Bennai Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 139 101 0 04 Jan 2021
On Baselines for Local Feature Attributions Johannes Haug Stefan Zurn Peter El-Jiz Gjergji Kasneci FAtt 62 31 0 04 Jan 2021
iGOS++: Integrated Gradient Optimized Saliency by Bilateral Perturbations Saeed Khorram T. Lawson Fuxin Li AAML FAtt 59 26 0 31 Dec 2020
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging Han Guo Nazneen Rajani Peter Hase Joey Tianyi Zhou Caiming Xiong TDI 135 116 0 31 Dec 2020
Quantitative Evaluations on Saliency Methods: An Experimental Study Xiao-hui Li Yuhan Shi Haoyang Li Wei Bai Yuanwei Song Caleb Chen Cao Lei Chen FAtt XAI 108 20 0 31 Dec 2020
SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with Uncertainty Estimation and Explainability R. Singh R. Gorantla Sai Giridhar Allada N. Pratap 67 3 0 30 Dec 2020
Enhanced Regularizers for Attributional Robustness A. Sarkar Anirban Sarkar V. Balasubramanian 65 16 0 28 Dec 2020
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 209 691 0 28 Dec 2020
Explaining NLP Models via Minimal Contrastive Editing (MiCE) Alexis Ross Ana Marasović Matthew E. Peters 77 122 0 27 Dec 2020
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring Mechanism Swapnil Parekh Yaman Kumar Singla Changyou Chen Junyi Jessy Li R. Shah 76 11 0 27 Dec 2020
Inserting Information Bottlenecks for Attribution in Transformers Zhiying Jiang Raphael Tang Ji Xin Jimmy J. Lin 55 6 0 27 Dec 2020
To what extent do human explanations of model behavior align with actual model behavior? Grusha Prasad Yixin Nie Joey Tianyi Zhou Robin Jia Douwe Kiela Adina Williams 73 28 0 24 Dec 2020
QUACKIE: A NLP Classification Task With Ground Truth Explanations Yves Rychener X. Renard Djamé Seddah P. Frossard Marcin Detyniecki 34 3 0 24 Dec 2020
Algorithmic Recourse in the Wild: Understanding the Impact of Data and Model Shifts Kaivalya Rawal Ece Kamar Himabindu Lakkaraju 96 42 0 22 Dec 2020
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 96 64 0 18 Dec 2020
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 145 681 0 17 Dec 2020
Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN N. Yudistira M. Kavitha Takio Kurita 3DPC 66 13 0 17 Dec 2020