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A Unified Approach to Interpreting Model Predictions

22 May 2017

Papers citing "A Unified Approach to Interpreting Model Predictions"

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Title
Local Explanation of Dialogue Response Generation Yi-Lin Tuan Connor Pryor Wenhu Chen Lise Getoor Wenjie Wang 86 12 0 11 Jun 2021
Verifying Quantized Neural Networks using SMT-Based Model Checking Luiz Sena Xidan Song E. Alves I. Bessa Edoardo Manino Lucas C. Cordeiro Eddie Batista de Lima Filho 69 11 0 10 Jun 2021
On the overlooked issue of defining explanation objectives for local-surrogate explainers Rafael Poyiadzi X. Renard Thibault Laugel Raúl Santos-Rodríguez Marcin Detyniecki 50 6 0 10 Jun 2021
A Deep Variational Approach to Clustering Survival Data Laura Manduchi Ricards Marcinkevics M. Massi Thomas Weikert Alexander Sauter ... F. Vasella M. Neidert M. Pfister Bram Stieltjes Julia E. Vogt 146 31 0 10 Jun 2021
Explainable AI, but explainable to whom? Julie Gerlings Millie Søndergaard Jensen Arisa Shollo 82 43 0 10 Jun 2021
Explaining Time Series Predictions with Dynamic Masks Jonathan Crabbé M. Schaar FAtt AI4TS 104 81 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 95 32 0 09 Jun 2021
On the Lack of Robust Interpretability of Neural Text Classifiers Muhammad Bilal Zafar Michele Donini Dylan Slack Cédric Archambeau Sanjiv Ranjan Das K. Kenthapadi AAML 70 21 0 08 Jun 2021
Accurate Shapley Values for explaining tree-based models Salim I. Amoukou Nicolas Brunel Tangi Salaun TDI FAtt 75 15 0 07 Jun 2021
How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements Chen Shani Nadav Borenstein Dafna Shahaf 55 4 0 06 Jun 2021
Causal Abstractions of Neural Networks Atticus Geiger Hanson Lu Thomas Icard Christopher Potts NAI CML 80 246 0 06 Jun 2021
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning Yatao Bian Yu Rong Tingyang Xu Jiaxiang Wu Andreas Krause Junzhou Huang 126 16 0 05 Jun 2021
Counterfactual Explanations Can Be Manipulated Dylan Slack Sophie Hilgard Himabindu Lakkaraju Sameer Singh 94 138 0 04 Jun 2021
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures N. Vadori Rahul Savani Thomas Spooner Sumitra Ganesh 83 4 0 04 Jun 2021
Towards an Explanation Space to Align Humans and Explainable-AI Teamwork G. Cabour A. Morales É. Ledoux S. Bassetto 56 5 0 02 Jun 2021
On Efficiently Explaining Graph-Based Classifiers Xuanxiang Huang Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 118 39 0 02 Jun 2021
Towards Robust Classification Model by Counterfactual and Invariant Data Generation C. Chang George Adam Anna Goldenberg OOD CML 73 32 0 02 Jun 2021
When and Why does a Model Fail? A Human-in-the-loop Error Detection Framework for Sentiment Analysis Zhe Liu Yufan Guo J. Mahmud 88 10 0 02 Jun 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations Peter Hase Harry Xie Joey Tianyi Zhou OODD LRM FAtt 128 91 0 01 Jun 2021
Information Theoretic Measures for Fairness-aware Feature Selection S. Khodadadian M. Nafea AmirEmad Ghassami Negar Kiyavash 63 8 0 01 Jun 2021
Efficient Explanations With Relevant Sets Yacine Izza Alexey Ignatiev Nina Narodytska Martin C. Cooper Sasha Rubin FAtt 94 16 0 01 Jun 2021
To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods E. Amparore Alan Perotti P. Bajardi FAtt 88 68 0 01 Jun 2021
Explanations for Monotonic Classifiers Sasha Rubin Thomas Gerspacher M. Cooper Alexey Ignatiev Nina Narodytska FAtt 101 46 0 01 Jun 2021
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals Asma Ghandeharioun Been Kim Chun-Liang Li Brendan Jou B. Eoff Rosalind W. Picard AAML 102 54 0 31 May 2021
SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning Jianhong Wang Yuan Zhang Yunjie Gu Tae-Kyun Kim OffRL FAtt 84 23 0 31 May 2021
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores Giang Nguyen Daeyoung Kim Anh Totti Nguyen FAtt 144 89 0 31 May 2021
Bounded logit attention: Learning to explain image classifiers Thomas Baumhauer D. Slijepcevic Matthias Zeppelzauer FAtt 66 2 0 31 May 2021
An exact counterfactual-example-based approach to tree-ensemble models interpretability P. Blanchart 60 4 0 31 May 2021
Attention Flows are Shapley Value Explanations Kawin Ethayarajh Dan Jurafsky FAtt TDI 86 35 0 31 May 2021
A General Taylor Framework for Unifying and Revisiting Attribution Methods Huiqi Deng Na Zou Mengnan Du Weifu Chen Guo-Can Feng Helen Zhou TDI FAtt 81 2 0 28 May 2021
Do not explain without context: addressing the blind spot of model explanations Katarzyna Wo'znica Katarzyna Pkekala Hubert Baniecki Wojciech Kretowicz El.zbieta Sienkiewicz P. Biecek 66 1 0 28 May 2021
XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data Eloise Withnell Xiaoyu Zhang Kai Sun Yike Guo 78 67 0 26 May 2021
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs Mohammad Malekzadeh Anastasia Borovykh Deniz Gündüz MIACV 87 42 0 25 May 2021
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests Clément Bénard Gérard Biau Sébastien Da Veiga Erwan Scornet FAtt 100 32 0 25 May 2021
Argumentative XAI: A Survey Kristijonas vCyras Antonio Rago Emanuele Albini P. Baroni Francesca Toni 76 144 0 24 May 2021
On Explaining Random Forests with SAT Yacine Izza Sasha Rubin FAtt 123 75 0 21 May 2021
Explainable Machine Learning with Prior Knowledge: An Overview Katharina Beckh Sebastian Müller Matthias Jakobs Vanessa Toborek Hanxiao Tan Raphael Fischer Pascal Welke Sebastian Houben Laura von Rueden XAI 89 28 0 21 May 2021
Probabilistic Sufficient Explanations Eric Wang Pasha Khosravi Guy Van den Broeck XAI FAtt TPM 176 25 0 21 May 2021
Explainable Activity Recognition for Smart Home Systems Devleena Das Yasutaka Nishimura R. Vivek Naoto Takeda Sean T. Fish Thomas Ploetz Sonia Chernova 47 43 0 20 May 2021
Evaluating the Correctness of Explainable AI Algorithms for Classification Orcun Yalcin Xiuyi Fan Siyuan Liu XAI FAtt 53 15 0 20 May 2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks Thorben Funke Megha Khosla Mandeep Rathee Avishek Anand FAtt 105 41 0 18 May 2021
Algorithm-Agnostic Explainability for Unsupervised Clustering Charles A. Ellis M. Sendi Eloy P. T. Geenjaar Sergey Plis Robyn L. Miller Vince D. Calhoun 88 25 0 17 May 2021
Fine-grained Interpretation and Causation Analysis in Deep NLP Models Hassan Sajjad Narine Kokhlikyan Fahim Dalvi Nadir Durrani MILM 85 8 0 17 May 2021
CNN-based Approaches For Cross-Subject Classification in Motor Imagery: From The State-of-The-Art to DynamicNet Alberto Zancanaro Giulia Cisotto J. Paulo G. Pires U. J. Nunes 76 27 0 17 May 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 138 142 0 17 May 2021
Abstraction, Validation, and Generalization for Explainable Artificial Intelligence Scott Cheng-Hsin Yang Tomas Folke Patrick Shafto 74 5 0 16 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 155 198 0 15 May 2021
Cohort Shapley value for algorithmic fairness Masayoshi Mase Art B. Owen Benjamin B. Seiler 112 14 0 15 May 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 64 0 0 14 May 2021
Quantified Sleep: Machine learning techniques for observational n-of-1 studies G. Truda AI4TS 19 2 0 14 May 2021