Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations

19 May 2019

Papers citing "Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations"

27 / 177 papers shown

Title
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 37 55 0 18 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 47 176 0 07 Mar 2021
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs Harini Suresh Kathleen M. Lewis John Guttag Arvind Satyanarayan FAtt 40 25 0 17 Feb 2021
Towards Designing Computer Vision-based Explainable-AI Solution: A Use Case of Livestock Mart Industry Devam Dave Het Naik Smiti Singhal Rudresh Dwivedi Pankesh Patel 20 1 0 08 Feb 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 65 100 0 11 Jan 2021
GeCo: Quality Counterfactual Explanations in Real Time Maximilian Schleich Zixuan Geng Yihong Zhang D. Suciu 46 61 0 05 Jan 2021
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging Han Guo Nazneen Rajani Peter Hase Joey Tianyi Zhou Caiming Xiong TDI 41 102 0 31 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 20 397 0 19 Oct 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations Andrea Ferrario M. Loi 25 5 0 09 Oct 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 19 89 0 28 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 38 62 0 11 Sep 2020
Model extraction from counterfactual explanations Ulrich Aïvodji Alexandre Bolot Sébastien Gambs MIACV MLAU 30 51 0 03 Sep 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
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 25 85 0 23 Jun 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 28 178 0 11 Jun 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 27 213 0 09 Mar 2020
ViCE: Visual Counterfactual Explanations for Machine Learning Models Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML 57 93 0 05 Mar 2020
Learning Global Transparent Models Consistent with Local Contrastive Explanations Tejaswini Pedapati Avinash Balakrishnan Karthikeyan Shanmugam Amit Dhurandhar FAtt 22 0 0 19 Feb 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 24 337 0 14 Feb 2020
Decisions, Counterfactual Explanations and Strategic Behavior Stratis Tsirtsis Manuel Gomez Rodriguez 27 58 0 11 Feb 2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans Vivian Lai Han Liu Chenhao Tan 35 138 0 14 Jan 2020
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 52 702 0 08 Jan 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 22 206 0 06 Dec 2019
Explaining Visual Models by Causal Attribution Álvaro Parafita Jordi Vitrià CML FAtt 62 35 0 19 Sep 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 29 378 0 03 Jul 2019
Determinantal point processes for machine learning Alex Kulesza B. Taskar 162 1,123 0 25 Jul 2012