Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations

19 May 2019

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

50 / 177 papers shown

Title
Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space Eric Yeh Pedro Sequeira Jesse Hostetler Melinda Gervasio OOD CML BDL OffRL 19 2 0 15 Jul 2022
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs Vinitra Swamy Bahar Radmehr Natasa Krco Mirko Marras Tanja Kaser FAtt ELM 11 39 0 01 Jul 2022
Use-Case-Grounded Simulations for Explanation Evaluation Valerie Chen Nari Johnson Nicholay Topin Gregory Plumb Ameet Talwalkar FAtt ELM 22 24 0 05 Jun 2022
PROMISSING: Pruning Missing Values in Neural Networks S. M. Kia N. M. Rad Dan Opstal B. V. Schie A. Marquand J. Pluim W. Cahn H. Schnack VLM 29 4 0 03 Jun 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation Wenzhuo Yang Jia Li Caiming Xiong S. Hoi CML 35 13 0 31 May 2022
Causal Explanations for Sequential Decision Making Under Uncertainty Samer B. Nashed Saaduddin Mahmud C. V. Goldman S. Zilberstein CML 43 4 0 30 May 2022
Justifying Social-Choice Mechanism Outcome for Improving Participant Satisfaction Sharadhi Alape Suryanarayana David Sarne Bar-Ilan 19 7 0 24 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 30 26 0 16 May 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models Xiaoting Shao Kristian Kersting BDL 22 1 0 16 May 2022
An Explainable Regression Framework for Predicting Remaining Useful Life of Machines Talhat Khan Kashif Ahmad Jebran Khan Imran Khan Nasir Ahmad 43 13 0 28 Apr 2022
Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI Greta Warren Mark T. Keane R. Byrne CML 27 22 0 21 Apr 2022
Diffusion Models for Counterfactual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 32 55 0 29 Mar 2022
On the Computation of Necessary and Sufficient Explanations Adnan Darwiche Chunxi Ji FAtt 13 19 0 20 Mar 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk Teresa Datta Johannes van-den-Heuvel Gjergji Kasneci Himabindu Lakkaraju 24 38 0 13 Mar 2022
Evaluation Methods and Measures for Causal Learning Algorithms Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 24 51 0 07 Feb 2022
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners K. Ramamurthy Amit Dhurandhar Dennis L. Wei Zaid Bin Tariq FAtt 38 3 0 02 Feb 2022
Counterfactual Plans under Distributional Ambiguity N. Bui D. Nguyen Viet Anh Nguyen 62 24 0 29 Jan 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 39 77 0 25 Jan 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis Giovanni De Toni Bruno Lepri Andrea Passerini CML 30 13 0 18 Jan 2022
Interpretable Low-Resource Legal Decision Making R. Bhambhoria Hui Liu Samuel Dahan Xiao-Dan Zhu ELM AILaw 27 9 0 01 Jan 2022
Towards a Shapley Value Graph Framework for Medical peer-influence J. Duell M. Seisenberger Gert Aarts Shang-Ming Zhou Xiuyi Fan 16 0 0 29 Dec 2021
Towards Relatable Explainable AI with the Perceptual Process Wencan Zhang Brian Y. Lim AAML XAI 25 62 0 28 Dec 2021
Prolog-based agnostic explanation module for structured pattern classification Gonzalo Nápoles Fabian Hoitsma A. Knoben A. Jastrzębska Maikel Leon Espinosa 17 13 0 23 Dec 2021
Post-discovery Analysis of Anomalous Subsets I. Mulang' William Ogallo G. Tadesse Aisha Walcott-Bryant 29 1 0 23 Nov 2021
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications Adrien Bennetot Ivan Donadello Ayoub El Qadi M. Dragoni Thomas Frossard ... M. Trocan Raja Chatila Andreas Holzinger Artur Garcez Natalia Díaz Rodríguez XAI 32 7 0 13 Nov 2021
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation M. Temraz Markt. Keane 21 42 0 05 Nov 2021
Data Synthesis for Testing Black-Box Machine Learning Models Diptikalyan Saha Aniya Aggarwal Sandeep Hans 17 4 0 03 Nov 2021
On Quantitative Evaluations of Counterfactuals Frederik Hvilshoj Alexandros Iosifidis Ira Assent 19 10 0 30 Oct 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 26 49 0 27 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 36 647 0 05 Oct 2021
Discriminative Attribution from Counterfactuals N. Eckstein A. S. Bates G. Jefferis Jan Funke FAtt CML 27 1 0 28 Sep 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 46 5 0 15 Sep 2021
Model Explanations via the Axiomatic Causal Lens Gagan Biradar Vignesh Viswanathan Yair Zick XAI CML 25 1 0 08 Sep 2021
Counterfactual Evaluation for Explainable AI Yingqiang Ge Shuchang Liu Zelong Li Shuyuan Xu Shijie Geng Yunqi Li Juntao Tan Fei Sun Yongfeng Zhang CML 38 13 0 05 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond Amir Feder Katherine A. Keith Emaad A. Manzoor Reid Pryzant Dhanya Sridhar ... Roi Reichart Margaret E. Roberts Brandon M Stewart Victor Veitch Diyi Yang CML 41 234 0 02 Sep 2021
Feature Recommendation for Structural Equation Model Discovery in Process Mining Mahnaz Sadat Qafari Wil M.P. van der Aalst 17 7 0 13 Aug 2021
Improving Visualization Interpretation Using Counterfactuals Smiti Kaul D. Borland Nan Cao David Gotz CML 10 17 0 21 Jul 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 37 33 0 09 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
Rational Shapley Values David S. Watson 23 20 0 18 Jun 2021
Optimal Counterfactual Explanations in Tree Ensembles Axel Parmentier Thibaut Vidal 19 54 0 11 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 18 91 0 01 Jun 2021
A unified logical framework for explanations in classifier systems Xinghan Liu E. Lorini 15 12 0 30 May 2021
Counterfactual Explanations for Neural Recommenders Khanh Tran Azin Ghazimatin Rishiraj Saha Roy AAML CML 54 65 0 11 May 2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang Yossi Gandelsman Michal Yarom Yoav Wald G. Elidan ... William T. Freeman Phillip Isola Amir Globerson Michal Irani Inbar Mosseri GAN 45 152 0 27 Apr 2021
Optimal Counterfactual Explanations for Scorecard modelling Guillermo Navas-Palencia 11 9 0 17 Apr 2021
Consequence-aware Sequential Counterfactual Generation Philip Naumann Eirini Ntoutsi OffRL 17 24 0 12 Apr 2021
Explaining the Road Not Taken Hua Shen Ting-Hao 'Kenneth' Huang FAtt XAI 27 9 0 27 Mar 2021