The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations

22 July 2019

Papers citing "The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations"

50 / 102 papers shown

Title
Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box Catarina Moreira Yu-Liang Chou Chih-Jou Hsieh Chun Ouyang Joaquim A. Jorge João Pereira CML 83 9 0 04 Mar 2022
Sensing accident-prone features in urban scenes for proactive driving and accident prevention Sumit Mishra Praveenbalaji Rajendran L. Vecchietti Dongsoo Har 57 13 0 25 Feb 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 92 36 0 22 Jan 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 178 422 0 20 Jan 2022
Verifying Controllers with Convolutional Neural Network-based Perception: A Case for Intelligible, Safe, and Precise Abstractions Chiao Hsieh Keyur Joshi Sasa Misailovic Sayan Mitra 87 35 0 10 Nov 2021
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation M. Temraz Markt. Keane 70 45 0 05 Nov 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 94 51 0 27 Oct 2021
CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations P. Rasouli Ingrid Chieh Yu 45 27 0 18 Aug 2021
On the Importance of Domain-specific Explanations in AI-based Cybersecurity Systems (Technical Report) José Paredes J. C. Teze Gerardo Simari Maria Vanina Martinez 70 20 0 02 Aug 2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms Martin Pawelczyk Sascha Bielawski J. V. D. Heuvel Tobias Richter Gjergji Kasneci CML 83 105 0 02 Aug 2021
Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies F. Xie Han Yuan Yilin Ning M. Ong Mengling Feng Wynne Hsu B. Chakraborty Nan Liu 97 89 0 21 Jul 2021
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions Eoin Delaney Derek Greene Mark T. Keane 74 26 0 20 Jul 2021
Personalized and Reliable Decision Sets: Enhancing Interpretability in Clinical Decision Support Systems Francisco Valente Simão Paredes J. Henriques 17 1 0 15 Jul 2021
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations Bodhisattwa Prasad Majumder Oana-Maria Camburu Thomas Lukasiewicz Julian McAuley 96 36 0 25 Jun 2021
Interpretable Machine Learning Classifiers for Brain Tumour Survival Prediction C. Charlton M. Poon P. Brennan Jacques D. Fleuriot 23 0 0 17 Jun 2021
Characterizing the risk of fairwashing Ulrich Aïvodji Hiromi Arai Sébastien Gambs Satoshi Hara 92 28 0 14 Jun 2021
Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning Tong Wang Jingyi Yang Yunyi Li Boxiang Wang FAtt 60 5 0 06 May 2021
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation Markt. Keane Eoin M. Kenny M. Temraz Derek Greene Barry Smyth 55 5 0 29 Apr 2021
Individual Explanations in Machine Learning Models: A Case Study on Poverty Estimation Alfredo Carrillo Luis F. Cantú Luis Tejerina Alejandro Noriega 16 3 0 09 Apr 2021
Individual Explanations in Machine Learning Models: A Survey for Practitioners Alfredo Carrillo Luis F. Cantú Alejandro Noriega FaML 31 15 0 09 Apr 2021
Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability Pushkar Mishra H. Yannakoudakis Ekaterina Shutova 60 7 0 31 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 240 677 0 20 Mar 2021
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties Lisa Schut Oscar Key R. McGrath Luca Costabello Bogdan Sacaleanu Medb Corcoran Y. Gal CML 105 48 0 16 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 165 179 0 07 Mar 2021
Human-Understandable Decision Making for Visual Recognition Xiaowei Zhou Jie Yin Ivor Tsang Chen Wang FAtt HAI 54 1 0 05 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 94 146 0 26 Feb 2021
A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations Barry Smyth Mark T. Keane CML 96 27 0 22 Jan 2021
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning Jiaheng Xie Xinyu Liu HAI 55 10 0 21 Dec 2020
Sparse encoding for more-interpretable feature-selecting representations in probabilistic matrix factorization Joshua C. Chang P. Fletcher Ju Han Ted L.Chang Shashaank Vattikuti Bart Desmet Ayah Zirikly Carson C. Chow 37 4 0 08 Dec 2020
Shapley values for cluster importance: How clusters of the training data affect a prediction A. Brandsæter I. Glad TDI FAtt 61 6 0 07 Dec 2020
Challenging common interpretability assumptions in feature attribution explanations Jonathan Dinu Jeffrey P. Bigham J. Z. K. Unaffiliated 75 14 0 04 Dec 2020
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 190 269 0 03 Dec 2020
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 176 176 0 20 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 111 405 0 19 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 70 172 0 08 Oct 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 53 91 0 28 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 102 64 0 11 Sep 2020
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning Eoin M. Kenny Mark T. Keane 70 102 0 10 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 87 52 0 03 Sep 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 195 643 0 01 Jul 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 144 87 0 23 Jun 2020
Explainable Artificial Intelligence: a Systematic Review Giulia Vilone Luca Longo XAI 110 271 0 29 May 2020
Good Counterfactuals and Where to Find Them: A Case-Based Technique for Generating Counterfactuals for Explainable AI (XAI) Mark T. Keane Barry Smyth CML 76 146 0 26 May 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 62 18 0 05 May 2020
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks Giyoung Jeon Haedong Jeong Jaesik Choi 34 13 0 12 Dec 2019
Explainability Fact Sheets: A Framework for Systematic Assessment of Explainable Approaches Kacper Sokol Peter A. Flach XAI 119 304 0 11 Dec 2019
Identifying the Most Explainable Classifier Brett Mullins FAtt 42 1 0 18 Oct 2019
Model-Agnostic Linear Competitors -- When Interpretable Models Compete and Collaborate with Black-Box Models Hassan Rafique Tong Wang Qihang Lin 41 4 0 23 Sep 2019
Predictive Multiplicity in Classification Charles Marx Flavio du Pin Calmon Berk Ustun 136 147 0 14 Sep 2019
Learning Fair Rule Lists Ulrich Aïvodji Julien Ferry Sébastien Gambs Marie-José Huguet Mohamed Siala FaML 55 11 0 09 Sep 2019