Learning to Explain: An Information-Theoretic Perspective on Model Interpretation

21 February 2018

Papers citing "Learning to Explain: An Information-Theoretic Perspective on Model Interpretation"

50 / 302 papers shown

Title
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 144 665 0 28 Dec 2020
Get It Scored Using AutoSAS -- An Automated System for Scoring Short Answers Yaman Kumar Singla Swati Aggarwal Debanjan Mahata R. Shah Ponnurangam Kumaraguru Roger Zimmermann 26 56 0 21 Dec 2020
Learning from the Best: Rationalizing Prediction by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 133 35 0 16 Dec 2020
E2E-FS: An End-to-End Feature Selection Method for Neural Networks Brais Cancela V. Bolón-Canedo Amparo Alonso-Betanzos 18 9 0 14 Dec 2020
Synthetic Data: Opening the data floodgates to enable faster, more directed development of machine learning methods James Jordon A. Wilson M. Schaar AI4CE 87 16 0 08 Dec 2020
Challenging common interpretability assumptions in feature attribution explanations Jonathan Dinu Jeffrey P. Bigham J. Z. K. Unaffiliated 16 14 0 04 Dec 2020
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals Tsung-Yu Hsieh Suhang Wang Yiwei Sun Vasant Honavar BDL AI4TS FAtt 18 9 0 23 Nov 2020
Interpretable Visual Reasoning via Induced Symbolic Space Zhonghao Wang Kai Wang Mo Yu Jinjun Xiong Wen-mei W. Hwu M. Hasegawa-Johnson Humphrey Shi LRM OCL 16 19 0 23 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 48 243 0 21 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 43 8 0 18 Nov 2020
Learning outside the Black-Box: The pursuit of interpretable models Jonathan Crabbé Yao Zhang W. Zame M. Schaar 6 24 0 17 Nov 2020
Parameterized Explainer for Graph Neural Network Dongsheng Luo Wei Cheng Dongkuan Xu Wenchao Yu Bo Zong Haifeng Chen Xiang Zhang 53 542 0 09 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 33 33 0 06 Nov 2020
MAIRE -- A Model-Agnostic Interpretable Rule Extraction Procedure for Explaining Classifiers Rajat Sharma N. Reddy V. Kamakshi N. C. Krishnan Shweta Jain FAtt 27 7 0 03 Nov 2020
Bayesian Importance of Features (BIF) Kamil Adamczewski Frederik Harder Mijung Park FAtt 15 2 0 26 Oct 2020
A Framework to Learn with Interpretation Jayneel Parekh Pavlo Mozharovskyi Florence dÁlché-Buc AI4CE FAtt 25 30 0 19 Oct 2020
Human-interpretable model explainability on high-dimensional data Damien de Mijolla Christopher Frye M. Kunesch J. Mansir Ilya Feige FAtt 25 8 0 14 Oct 2020
Learning Propagation Rules for Attribution Map Generation Yiding Yang Jiayan Qiu Xiuming Zhang Dacheng Tao Xinchao Wang FAtt 38 17 0 14 Oct 2020
Explain2Attack: Text Adversarial Attacks via Cross-Domain Interpretability M. Hossam Trung Le He Zhao Dinh Q. Phung SILM AAML 13 6 0 14 Oct 2020
Learning to Attack with Fewer Pixels: A Probabilistic Post-hoc Framework for Refining Arbitrary Dense Adversarial Attacks He Zhao Thanh-Tuan Nguyen Trung Le Paul Montague O. Vel Tamas Abraham Dinh Q. Phung AAML 24 2 0 13 Oct 2020
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 33 26 0 04 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 15 63 0 01 Oct 2020
Information-Theoretic Visual Explanation for Black-Box Classifiers Jihun Yi Eunji Kim Siwon Kim Sungroh Yoon FAtt 25 6 0 23 Sep 2020
The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets Oana-Maria Camburu Eleonora Giunchiglia Jakob N. Foerster Thomas Lukasiewicz Phil Blunsom FAtt 23 23 0 23 Sep 2020
Explainable Empirical Risk Minimization Linli Zhang Georgios Karakasidis Arina Odnoblyudova Leyla Dogruel Alex Jung 27 5 0 03 Sep 2020
ALEX: Active Learning based Enhancement of a Model's Explainability Ishani Mondal Debasis Ganguly 9 2 0 02 Sep 2020
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models Thanh Nguyen-Duc He Zhao Jianfei Cai Dinh Q. Phung VLM MedIm 33 4 0 06 Aug 2020
When is invariance useful in an Out-of-Distribution Generalization problem ? Masanori Koyama Shoichiro Yamaguchi OOD 34 65 0 04 Aug 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution A. Khademi Vasant Honavar CML 20 9 0 01 Aug 2020
Gaussian Process Regression with Local Explanation Yuya Yoshikawa Tomoharu Iwata FAtt 13 18 0 03 Jul 2020
Interpreting and Disentangling Feature Components of Various Complexity from DNNs Jie Ren Mingjie Li Zexu Liu Quanshi Zhang CoGe 19 18 0 29 Jun 2020
Set Based Stochastic Subsampling Bruno Andreis Seanie Lee A. Nguyen Juho Lee Eunho Yang Sung Ju Hwang BDL 14 0 0 25 Jun 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 30 73 0 24 Jun 2020
How does this interaction affect me? Interpretable attribution for feature interactions Michael Tsang Sirisha Rambhatla Yan Liu FAtt 22 85 0 19 Jun 2020
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 38 85 0 15 Jun 2020
Explaining Predictions by Approximating the Local Decision Boundary G. Vlassopoulos T. Erven Henry Brighton Vlado Menkovski FAtt 25 8 0 14 Jun 2020
DNF-Net: A Neural Architecture for Tabular Data A. Abutbul G. Elidan L. Katzir Ran El-Yaniv LMTD AI4CE 24 29 0 11 Jun 2020
Why Attentions May Not Be Interpretable? Bing Bai Jian Liang Guanhua Zhang Hao Li Kun Bai Fei Wang FAtt 25 56 0 10 Jun 2020
Neural Methods for Point-wise Dependency Estimation Yao-Hung Hubert Tsai Han Zhao M. Yamada Louis-Philippe Morency Ruslan Salakhutdinov 33 31 0 09 Jun 2020
Adversarial Infidelity Learning for Model Interpretation Jian Liang Bing Bai Yuren Cao Kun Bai Fei Wang AAML 54 18 0 09 Jun 2020
Aligning Faithful Interpretations with their Social Attribution Alon Jacovi Yoav Goldberg 23 105 0 01 Jun 2020
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport Kyle Swanson L. Yu Tao Lei OT 29 37 0 27 May 2020
NILE : Natural Language Inference with Faithful Natural Language Explanations Sawan Kumar Partha P. Talukdar XAI LRM 19 160 0 25 May 2020
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 33 219 0 01 May 2020
How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking Nicola De Cao M. Schlichtkrull Wilker Aziz Ivan Titov 25 90 0 30 Apr 2020
Multimodal Routing: Improving Local and Global Interpretability of Multimodal Language Analysis Yao-Hung Hubert Tsai Martin Q. Ma Muqiao Yang Ruslan Salakhutdinov Louis-Philippe Morency 12 4 0 29 Apr 2020
Invariant Rationalization Shiyu Chang Yang Zhang Mo Yu Tommi Jaakkola 202 201 0 22 Mar 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 21 150 0 16 Mar 2020
Neural Generators of Sparse Local Linear Models for Achieving both Accuracy and Interpretability Yuya Yoshikawa Tomoharu Iwata 16 7 0 13 Mar 2020
Explaining Knowledge Distillation by Quantifying the Knowledge Xu Cheng Zhefan Rao Yilan Chen Quanshi Zhang 18 119 0 07 Mar 2020