Towards Robust Interpretability with Self-Explaining Neural Networks

20 June 2018

David Alvarez-Melis

Papers citing "Towards Robust Interpretability with Self-Explaining Neural Networks"

50 / 507 papers shown

Title
Understanding Instance-based Interpretability of Variational Auto-Encoders Zhifeng Kong Kamalika Chaudhuri TDI 16 27 0 29 May 2021
The Definitions of Interpretability and Learning of Interpretable Models Weishen Pan Changshui Zhang FaML XAI 11 3 0 29 May 2021
How to Explain Neural Networks: an Approximation Perspective Hangcheng Dong Bingguo Liu Fengdong Chen Dong Ye Guodong Liu FAtt 12 1 0 17 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 29 0 0 14 May 2021
XAI Handbook: Towards a Unified Framework for Explainable AI Sebastián M. Palacio Adriano Lucieri Mohsin Munir Jörn Hees Sheraz Ahmed Andreas Dengel 25 32 0 14 May 2021
Sanity Simulations for Saliency Methods Joon Sik Kim Gregory Plumb Ameet Talwalkar FAtt 38 17 0 13 May 2021
Rationalization through Concepts Diego Antognini Boi Faltings FAtt 27 19 0 11 May 2021
From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence David Alvarez-Melis Harmanpreet Kaur Hal Daumé Hanna M. Wallach Jennifer Wortman Vaughan FAtt 51 27 0 27 Apr 2021
Weakly Supervised Multi-task Learning for Concept-based Explainability Catarina Belém Vladimir Balayan Pedro Saleiro P. Bizarro 81 10 0 26 Apr 2021
Improving Attribution Methods by Learning Submodular Functions Piyushi Manupriya Tarun Ram Menta S. Jagarlapudi V. Balasubramanian TDI 24 6 0 19 Apr 2021
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information Ioannis Mollas Nick Bassiliades Grigorios Tsoumakas 23 7 0 13 Apr 2021
Shapley Explanation Networks Rui Wang Xiaoqian Wang David I. Inouye TDI FAtt 24 44 0 06 Apr 2021
Explainability-aided Domain Generalization for Image Classification Robin M. Schmidt FAtt OOD 24 1 0 05 Apr 2021
NetAdaptV2: Efficient Neural Architecture Search with Fast Super-Network Training and Architecture Optimization Tien-Ju Yang Yi-Lun Liao Vivienne Sze 21 25 0 31 Mar 2021
Efficient Explanations from Empirical Explainers Robert Schwarzenberg Nils Feldhus Sebastian Möller FAtt 32 9 0 29 Mar 2021
Building Reliable Explanations of Unreliable Neural Networks: Locally Smoothing Perspective of Model Interpretation Dohun Lim Hyeonseok Lee Sungchan Kim FAtt AAML 23 13 0 26 Mar 2021
SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers Dheeraj Rajagopal Vidhisha Balachandran Eduard H. Hovy Yulia Tsvetkov MILM SSL FAtt AI4TS 16 65 0 23 Mar 2021
Weakly Supervised Recovery of Semantic Attributes Ameen Ali Tomer Galanti Evgeniy Zheltonozhskiy Chaim Baskin Lior Wolf 34 0 0 22 Mar 2021
XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanations Eunji Kim Siwon Kim Minji Seo Sungroh Yoon ViT FAtt 16 113 0 19 Mar 2021
Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction Aniruddh Raghu John Guttag K. Young E. Pomerantsev Adrian V. Dalca Collin M. Stultz 13 9 0 04 Mar 2021
Evaluating Robustness of Counterfactual Explanations André Artelt Valerie Vaquet Riza Velioglu Fabian Hinder Johannes Brinkrolf M. Schilling Barbara Hammer 14 46 0 03 Mar 2021
Benchmarking and Survey of Explanation Methods for Black Box Models F. Bodria F. Giannotti Riccardo Guidotti Francesca Naretto D. Pedreschi S. Rinzivillo XAI 33 220 0 25 Feb 2021
Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing Sarah Wiegreffe Ana Marasović XAI 11 141 0 24 Feb 2021
DNN2LR: Automatic Feature Crossing for Credit Scoring Qiang Liu Zhaocheng Liu Haoli Zhang Yuntian Chen Jun Zhu 6 0 0 24 Feb 2021
Resilience of Bayesian Layer-Wise Explanations under Adversarial Attacks Ginevra Carbone G. Sanguinetti Luca Bortolussi FAtt AAML 21 4 0 22 Feb 2021
PatchX: Explaining Deep Models by Intelligible Pattern Patches for Time-series Classification Dominique Mercier Andreas Dengel Sheraz Ahmed AI4TS 12 5 0 11 Feb 2021
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement A. Ross Finale Doshi-Velez DRL 24 13 0 09 Feb 2021
Bandits for Learning to Explain from Explanations Freya Behrens Stefano Teso Davide Mottin FAtt 11 1 0 07 Feb 2021
Evaluating the Interpretability of Generative Models by Interactive Reconstruction A. Ross Nina Chen Elisa Zhao Hang Elena L. Glassman Finale Doshi-Velez 105 49 0 02 Feb 2021
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations Sérgio Jesus Catarina Belém Vladimir Balayan João Bento Pedro Saleiro P. Bizarro João Gama 136 120 0 21 Jan 2021
Interpretable Models for Granger Causality Using Self-explaining Neural Networks Ricards Marcinkevics Julia E. Vogt MILM CML 19 61 0 19 Jan 2021
U-Noise: Learnable Noise Masks for Interpretable Image Segmentation Teddy Koker Fatemehsadat Mireshghallah Tom Titcombe Georgios Kaissis 6 21 0 14 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 42 170 0 13 Jan 2021
Comprehensible Convolutional Neural Networks via Guided Concept Learning Sandareka Wickramanayake W. Hsu M. Lee SSL 17 23 0 11 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 81 100 0 04 Jan 2021
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 42 18 0 31 Dec 2020
Analyzing Representations inside Convolutional Neural Networks Uday Singh Saini Evangelos E. Papalexakis FAtt 19 2 0 23 Dec 2020
On Exploiting Hitting Sets for Model Reconciliation Stylianos Loukas Vasileiou Alessandro Previti William Yeoh 11 26 0 16 Dec 2020
Deep Argumentative Explanations Emanuele Albini Piyawat Lertvittayakumjorn Antonio Rago Francesca Toni AAML 21 4 0 10 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 43 38 0 03 Dec 2020
Teaching the Machine to Explain Itself using Domain Knowledge Vladimir Balayan Pedro Saleiro Catarina Belém L. Krippahl P. Bizarro 15 8 0 27 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
A Quantitative Perspective on Values of Domain Knowledge for Machine Learning Jianyi Yang Shaolei Ren FAtt FaML 6 5 0 17 Nov 2020
A Survey on the Explainability of Supervised Machine Learning Nadia Burkart Marco F. Huber FaML XAI 25 752 0 16 Nov 2020
GANMEX: One-vs-One Attributions Guided by GAN-based Counterfactual Explanation Baselines Sheng-Min Shih Pin-Ju Tien Zohar Karnin FAtt 11 14 0 11 Nov 2020
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes Herman Yau Chris Russell Simon Hadfield FAtt LRM 28 36 0 10 Nov 2020
Analyzing the tree-layer structure of Deep Forests Ludovic Arnould Claire Boyer Erwan Scornet Sorbonne Lpsm AI4CE 9 10 0 29 Oct 2020
Interpretable Machine Learning Models for Predicting and Explaining Vehicle Fuel Consumption Anomalies A. Barbado Óscar Corcho 14 11 0 28 Oct 2020
Now You See Me (CME): Concept-based Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lió Adrian Weller 25 72 0 25 Oct 2020