CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations

15 September 2021

Papers citing "CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations"

41 / 41 papers shown

Title
VCNet: A self-explaining model for realistic counterfactual generation Victor Guyomard Franccoise Fessant Thomas Guyet Tassadit Bouadi Alexandre Termier BDL OOD CML 44 25 0 21 Dec 2022
Preserving Fine-Grain Feature Information in Classification via Entropic Regularization Raphael Baena Lucas Drumetz Vincent Gripon 47 3 0 07 Aug 2022
Model-Based Counterfactual Synthesizer for Interpretation Fan Yang Sahan Suresh Alva Jiahao Chen X. Hu 40 31 0 16 Jun 2021
Amortized Generation of Sequential Algorithmic Recourses for Black-box Models Sahil Verma Keegan E. Hines John P. Dickerson 60 23 0 07 Jun 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 74 56 0 18 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 93 48 0 16 Mar 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 52 109 0 26 Feb 2021
Impact of Response Latency on User Behaviour in Mobile Web Search Ioannis Arapakis Souneil Park M. Pielot 30 13 0 22 Jan 2021
Learning Models for Actionable Recourse Alexis Ross Himabindu Lakkaraju Osbert Bastani FaML 75 19 0 12 Nov 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 79 402 0 19 Oct 2020
On the Fairness of Causal Algorithmic Recourse Julius von Kügelgen Amir-Hossein Karimi Umang Bhatt Isabel Valera Adrian Weller Bernhard Schölkopf FaML 111 85 0 13 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects Amir-Hossein Karimi Gilles Barthe Bernhard Schölkopf Isabel Valera FaML 68 172 0 08 Oct 2020
Do Wider Neural Networks Really Help Adversarial Robustness? Boxi Wu Jinghui Chen Deng Cai Xiaofei He Quanquan Gu AAML 59 95 0 03 Oct 2020
Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks Like Hui M. Belkin UQCV AAML VLM 48 171 0 12 Jun 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 49 340 0 14 Feb 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 95 206 0 06 Dec 2019
Explanation by Progressive Exaggeration Sumedha Singla Brian Pollack Junxiang Chen Kayhan Batmanghelich FAtt MedIm 67 103 0 01 Nov 2019
Learning Model-Agnostic Counterfactual Explanations for Tabular Data Martin Pawelczyk Johannes Haug Klaus Broelemann Gjergji Kasneci OOD CML 58 203 0 21 Oct 2019
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems Shalmali Joshi Oluwasanmi Koyejo Warut D. Vijitbenjaronk Been Kim Joydeep Ghosh FaML 60 187 0 22 Jul 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 72 384 0 03 Jul 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 108 1,021 0 19 May 2019
Actionable Recourse in Linear Classification Berk Ustun Alexander Spangher Yang Liu FaML 117 549 0 18 Sep 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 240 1,186 0 27 Jun 2018
Manipulating and Measuring Model Interpretability Forough Poursabzi-Sangdeh D. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna M. Wallach 86 698 0 21 Feb 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 115 589 0 21 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 124 3,961 0 06 Feb 2018
Ít's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao N. Shadbolt FaML 56 538 0 31 Jan 2018
Robust Loss Functions under Label Noise for Deep Neural Networks Aritra Ghosh Himanshu Kumar P. Sastry NoLa OOD 67 957 0 27 Dec 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 109 2,354 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 242 4,265 0 22 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 201 2,221 0 12 Jun 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 110 512 0 23 May 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,906 0 22 May 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 208 2,894 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 188 5,989 0 04 Mar 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 297 20,023 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 16,976 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Empirical Evaluation of Rectified Activations in Convolutional Network Bing Xu Naiyan Wang Tianqi Chen Mu Li 135 2,912 0 05 May 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014