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Axiomatic Attribution for Deep Networks

4 March 2017

Ankur Taly

Papers citing "Axiomatic Attribution for Deep Networks"

50 / 2,871 papers shown

Title
Visualizing Point Cloud Classifiers by Curvature Smoothing Ziwen Chen Wenxuan Wu Zhongang Qi Fuxin Li 3DPC 58 5 0 23 Nov 2019
Analysis of Deep Networks for Monocular Depth Estimation Through Adversarial Attacks with Proposal of a Defense Method Junjie Hu Takayuki Okatani AAML MDE 67 17 0 20 Nov 2019
Signed Input Regularization Saeid Asgari Taghanaki Kumar Abhishek Ghassan Hamarneh AAML 46 1 0 16 Nov 2019
Modelling EHR timeseries by restricting feature interaction Kun Zhang Yuan Xue Gerardo Flores A. Rajkomar Claire Cui Andrew M. Dai 35 6 0 14 Nov 2019
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images S. Kimeswenger Elisabeth Rumetshofer M. Hofmarcher P. Tschandl Harald Kittler Sepp Hochreiter W. Hötzenecker Günter Klambauer MedIm 45 5 0 14 Nov 2019
ERASER: A Benchmark to Evaluate Rationalized NLP Models Jay DeYoung Sarthak Jain Nazneen Rajani Eric P. Lehman Caiming Xiong R. Socher Byron C. Wallace 165 640 0 08 Nov 2019
Discovering Invariances in Healthcare Neural Networks M. T. Bahadori Layne Price OOD 23 0 0 08 Nov 2019
XDeep: An Interpretation Tool for Deep Neural Networks Fan Yang Zijian Zhang Haofan Wang Yuening Li Helen Zhou XAI HAI 37 2 0 04 Nov 2019
Feature relevance quantification in explainable AI: A causal problem Dominik Janzing Lenon Minorics Patrick Blobaum FAtt CML 109 286 0 29 Oct 2019
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control Mo Yu Shiyu Chang Yang Zhang Tommi Jaakkola 143 146 0 29 Oct 2019
Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models L. Brocki N. C. Chung FAtt 45 21 0 29 Oct 2019
A Game Theoretic Approach to Class-wise Selective Rationalization Shiyu Chang Yang Zhang Mo Yu Tommi Jaakkola 66 62 0 28 Oct 2019
Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks Aya Abdelsalam Ismail Mohamed K. Gunady L. Pessoa H. C. Bravo Soheil Feizi AI4TS 105 50 0 27 Oct 2019
CXPlain: Causal Explanations for Model Interpretation under Uncertainty Patrick Schwab W. Karlen FAtt CML 143 211 0 27 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 311 6,387 0 22 Oct 2019
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 106 150 0 22 Oct 2019
Contextual Prediction Difference Analysis for Explaining Individual Image Classifications Jindong Gu Volker Tresp FAtt 51 8 0 21 Oct 2019
Semantics for Global and Local Interpretation of Deep Neural Networks Jindong Gu Volker Tresp AI4CE 74 14 0 21 Oct 2019
Uncertainty-aware Sensitivity Analysis Using Rényi Divergences Topi Paananen Michael Riis Andersen Aki Vehtari 37 3 0 17 Oct 2019
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms Z. Q. Lin M. Shafiee S. Bochkarev Michael St. Jules Xiao Yu Wang A. Wong FAtt 83 81 0 16 Oct 2019
Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images C. González-Gonzalo B. Liefers Bram van Ginneken C. I. Sánchez MedIm 87 30 0 16 Oct 2019
Understanding Misclassifications by Attributes Sadaf Gulshad Zeynep Akata J. H. Metzen A. Smeulders AAML 95 0 0 15 Oct 2019
Whatcha lookin' at? DeepLIFTing BERT's Attention in Question Answering Ekaterina Arkhangelskaia Sourav Dutta AIMat 35 10 0 14 Oct 2019
Model Fusion via Optimal Transport Sidak Pal Singh Martin Jaggi MoMe FedML 186 241 0 12 Oct 2019
Explaining image classifiers by removing input features using generative models Chirag Agarwal Anh Totti Nguyen FAtt 100 15 0 09 Oct 2019
Interpretable Disentanglement of Neural Networks by Extracting Class-Specific Subnetwork Yulong Wang Xiaolin Hu Hang Su FAtt 56 1 0 07 Oct 2019
FastEstimator: A Deep Learning Library for Fast Prototyping and Productization Xiaomeng Dong Junpyo Hong Hsi-Ming Chang Michael Potter Aritra Chowdhury ... Rajesh Tamada Gaurav Kumar Caroline Favart V. R. Saripalli Gopal Avinash 23 2 0 07 Oct 2019
Testing and verification of neural-network-based safety-critical control software: A systematic literature review Jin Zhang Jingyue Li 85 48 0 05 Oct 2019
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Mehdi Neshat Zifan Wang Bradley Alexander Fan Yang Zijian Zhang Sirui Ding Markus Wagner Helen Zhou FAtt 114 1,078 0 03 Oct 2019
Leveraging Model Interpretability and Stability to increase Model Robustness Leilei Gan T. Michel Alexandre Briot AAML FAtt 36 1 0 01 Oct 2019
Synthesizing Action Sequences for Modifying Model Decisions Goutham Ramakrishnan Yun Chan Lee Aws Albarghouthi 121 33 0 30 Sep 2019
A Closer Look at Data Bias in Neural Extractive Summarization Models Ming Zhong Danqing Wang Pengfei Liu Xipeng Qiu Xuanjing Huang 105 42 0 30 Sep 2019
MonoNet: Towards Interpretable Models by Learning Monotonic Features An-phi Nguyen María Rodríguez Martínez FAtt 60 13 0 30 Sep 2019
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge Laura Rieger Chandan Singh W. James Murdoch Bin Yu FAtt 111 215 0 30 Sep 2019
Decision Explanation and Feature Importance for Invertible Networks Juntang Zhuang Nicha Dvornek Xiaoxiao Li Junlin Yang James S. Duncan AAML FAtt 61 5 0 30 Sep 2019
Interpreting Undesirable Pixels for Image Classification on Black-Box Models Sin-Han Kang Hong G Jung Seong-Whan Lee FAtt 52 3 0 27 Sep 2019
Towards Explainable Artificial Intelligence Wojciech Samek K. Müller XAI 96 449 0 26 Sep 2019
Deep Model Transferability from Attribution Maps Mingli Song Yixin Chen Xinchao Wang Chengchao Shen Xiuming Zhang 98 56 0 26 Sep 2019
Explaining and Interpreting LSTMs L. Arras Jose A. Arjona-Medina Michael Widrich G. Montavon Michael Gillhofer K. Müller Sepp Hochreiter Wojciech Samek FAtt AI4TS 76 79 0 25 Sep 2019
Switched linear projections for neural network interpretability Lech Szymanski B. McCane C. Atkinson FAtt MILM LLMSV 28 1 0 25 Sep 2019
AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models Eric Wallace Jens Tuyls Junlin Wang Sanjay Subramanian Matt Gardner Sameer Singh MILM 85 138 0 19 Sep 2019
Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification Fabian Eitel K. Ritter OOD FAtt 70 74 0 19 Sep 2019
Slices of Attention in Asynchronous Video Job Interviews Léo Hemamou G. Felhi Jean-Claude Martin Chloé Clavel 37 21 0 19 Sep 2019
The Explanation Game: Explaining Machine Learning Models Using Shapley Values Luke Merrick Ankur Taly FAtt TDI 59 33 0 17 Sep 2019
Identifying Pediatric Vascular Anomalies With Deep Learning Justin Chan Sharat Raju Randall Bly J. Perkins Shyamnath Gollakota 44 2 0 16 Sep 2019
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust Arjun Reddy Akula Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 71 18 0 15 Sep 2019
A deep learning system for differential diagnosis of skin diseases Yuan Liu Ayush Jain C. Eng David H. Way Kang Lee ... Dennis Ai Shijie Huang Yun-Hui Liu R. C. Dunn David Coz 53 609 0 11 Sep 2019
NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks Isaac Ahern Adam Noack Luis Guzman-Nateras Dejing Dou Boyang Albert Li Jun Huan FAtt 55 40 0 10 Sep 2019
Explainable Deep Learning for Video Recognition Tasks: A Framework & Recommendations Liam Hiley Alun D. Preece Y. Hicks XAI 39 15 0 07 Sep 2019
Improved Hierarchical Patient Classification with Language Model Pretraining over Clinical Notes Jonas Kemp A. Rajkomar Andrew M. Dai 75 10 0 06 Sep 2019