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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
Predicting Events in MOBA Games: Prediction, Attribution, and Evaluation Zelong Yang Yan Wang Piji Li Shaobin Lin Shuming Shi Shao-Lun Huang Wei Bi 118 13 0 17 Dec 2020
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification Martin Charachon C´eline Hudelot P. Cournède Camille Ruppli R. Ardon AAML GAN FAtt MedIm 25 7 0 14 Dec 2020
Demystifying Deep Neural Networks Through Interpretation: A Survey Giang Dao Minwoo Lee FaML FAtt 66 1 0 13 Dec 2020
Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network Jiayi Ji Yunpeng Luo Xiaoshuai Sun Fuhai Chen Gen Luo Yongjian Wu Yue Gao Rongrong Ji ViT 113 178 0 13 Dec 2020
Are We Ready For Learned Cardinality Estimation? Xiaoying Wang Changbo Qu Weiyuan Wu Jiannan Wang Qingqing Zhou 63 117 0 12 Dec 2020
Dependency Decomposition and a Reject Option for Explainable Models Jan Kronenberger Anselm Haselhoff FAtt AAML 67 8 0 11 Dec 2020
Understanding Learned Reward Functions Eric J. Michaud Adam Gleave Stuart J. Russell XAI OffRL 69 34 0 10 Dec 2020
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 72 18 0 10 Dec 2020
On Shapley Credit Allocation for Interpretability Debraj Basu FAtt 28 2 0 10 Dec 2020
On the Binding Problem in Artificial Neural Networks Klaus Greff Sjoerd van Steenkiste Jürgen Schmidhuber OCL 316 267 0 09 Dec 2020
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks U. Schlegel Daniela Oelke Daniel A. Keim Mennatallah El-Assady AI4TS 28 14 0 08 Dec 2020
A Singular Value Perspective on Model Robustness Malhar Jere Maghav Kumar F. Koushanfar AAML 86 6 0 07 Dec 2020
Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations Woo-Jeoung Nam Jaesik Choi Seong-Whan Lee FAtt AAML 40 14 0 07 Dec 2020
FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization Nishant Kumar Stefan Gumhold AAML MedIm 64 11 0 06 Dec 2020
Deep Learning for Medical Anomaly Detection -- A Survey Tharindu Fernando Harshala Gammulle Simon Denman Sridha Sridharan Clinton Fookes OOD 87 282 0 04 Dec 2020
Concept-based model explanations for Electronic Health Records Diana Mincu Eric Loreaux Shaobo Hou Sebastien Baur Ivan V. Protsyuk Martin G. Seneviratne A. Mottram Nenad Tomašev Alan Karthikesanlingam Jessica Schrouff 65 28 0 03 Dec 2020
Detecting Trojaned DNNs Using Counterfactual Attributions Karan Sikka Indranil Sur Susmit Jha Anirban Roy Ajay Divakaran AAML 38 13 0 03 Dec 2020
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization Shir Gur Ameen Ali Lior Wolf FAtt 68 37 0 03 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 90 121 0 03 Dec 2020
Understanding Failures of Deep Networks via Robust Feature Extraction Sahil Singla Besmira Nushi S. Shah Ece Kamar Eric Horvitz FAtt 98 84 0 03 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 76 36 0 03 Dec 2020
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training Andrei Margeloiu Nikola Simidjievski M. Jamnik Adrian Weller GAN AAML MedIm FAtt 52 18 0 02 Dec 2020
Evaluating Explanations: How much do explanations from the teacher aid students? Danish Pruthi Rachit Bansal Bhuwan Dhingra Livio Baldini Soares Michael Collins Zachary Chase Lipton Graham Neubig William W. Cohen FAtt XAI 117 110 0 01 Dec 2020
Rethinking Positive Aggregation and Propagation of Gradients in Gradient-based Saliency Methods Ashkan Khakzar Soroosh Baselizadeh Nassir Navab FAtt 36 8 0 01 Dec 2020
Towards Auditability for Fairness in Deep Learning Ivoline C. Ngong Krystal Maughan Joseph P. Near FedML 32 3 0 30 Nov 2020
Why model why? Assessing the strengths and limitations of LIME Jurgen Dieber S. Kirrane FAtt 94 104 0 30 Nov 2020
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations João Bento Pedro Saleiro André F. Cruz Mário A. T. Figueiredo P. Bizarro FAtt AI4TS 92 98 0 30 Nov 2020
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 75 116 0 29 Nov 2020
Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems Adriano Lucieri Muhammad Naseer Bajwa Andreas Dengel Sheraz Ahmed 136 10 0 26 Nov 2020
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization Sahil Suneja Yunhui Zheng Yufan Zhuang Jim Laredo Alessandro Morari AAML 71 34 0 25 Nov 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 103 112 0 25 Nov 2020
Play Fair: Frame Attributions in Video Models Will Price Dima Damen FAtt 55 5 0 24 Nov 2020
Detecting hidden signs of diabetes in external eye photographs Boris Babenko A. Mitani I. Traynis Naho Kitade Preeti Singh ... L. Peng D. Webster A. Varadarajan N. Hammel Yun-Hui Liu 51 59 0 23 Nov 2020
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging Abel Díaz Berenguer Hichem Sahli Boris Joukovsky Maryna Kvasnytsia Ine Dirks ... P. Meunier S. Gryspeerdt K. Smet B. Jansen Jef Vandemeulebroucke 74 9 0 23 Nov 2020
Interpreting Super-Resolution Networks with Local Attribution Maps Jinjin Gu Chao Dong FAtt SupR 73 228 0 22 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 151 252 0 21 Nov 2020
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision Kwanseok Oh Jee Seok Yoon Heung-Il Suk 48 4 0 20 Nov 2020
Data Representing Ground-Truth Explanations to Evaluate XAI Methods S. Amiri Rosina O. Weber Prateek Goel Owen Brooks Archer Gandley Brian Kitchell Aaron Zehm XAI 76 8 0 18 Nov 2020
Exploring Self-Attention for Visual Odometry H. Damirchi Rooholla Khorrambakht H. Taghirad 65 8 0 17 Nov 2020
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty Umang Bhatt Javier Antorán Yunfeng Zhang Q. V. Liao P. Sattigeri ... L. Nachman R. Chunara Madhulika Srikumar Adrian Weller Alice Xiang 146 252 0 15 Nov 2020
diagNNose: A Library for Neural Activation Analysis Jaap Jumelet AI4CE 46 9 0 13 Nov 2020
One Explanation is Not Enough: Structured Attention Graphs for Image Classification Vivswan Shitole Li Fuxin Minsuk Kahng Prasad Tadepalli Alan Fern FAtt GNN 70 38 0 13 Nov 2020
Roof fall hazard detection with convolutional neural networks using transfer learning E. Isleyen Sebnem Duzgun McKell R. Carter 23 3 0 12 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 65 84 0 12 Nov 2020
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making S. McGrath Parth Mehta Alexandra Zytek Isaac Lage Himabindu Lakkaraju UD 70 26 0 12 Nov 2020
GANMEX: One-vs-One Attributions Guided by GAN-based Counterfactual Explanation Baselines Sheng-Min Shih Pin-Ju Tien Zohar Karnin FAtt 86 14 0 11 Nov 2020
Debugging Tests for Model Explanations Julius Adebayo M. Muelly Ilaria Liccardi Been Kim FAtt 78 181 0 10 Nov 2020
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes Herman Yau Chris Russell Simon Hadfield FAtt LRM 58 38 0 10 Nov 2020
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End R. Mothilal Divyat Mahajan Chenhao Tan Amit Sharma FAtt CML 96 102 0 10 Nov 2020
Parameterized Explainer for Graph Neural Network Dongsheng Luo Wei Cheng Dongkuan Xu Wenchao Yu Bo Zong Haifeng Chen Xiang Zhang 149 567 0 09 Nov 2020