Counterfactual Explanations via Latent Space Projection and Interpolation

2 December 2021

Brian Barr

Matthew R. Harrington

Papers citing "Counterfactual Explanations via Latent Space Projection and Interpolation"

26 / 26 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 194 30,069 0 01 Mar 2022
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations R. Balasubramanian Samuel Sharpe Brian Barr J. Wittenbach C. Bayan Bruss BDL 21 18 0 16 Dec 2020
ViCE: Visual Counterfactual Explanations for Machine Learning Models Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML 75 96 0 05 Mar 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 254 10,591 0 17 Feb 2020
Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach Carlos Fernandez F. Provost Xintian Han CML 36 70 0 21 Jan 2020
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 89 206 0 06 Dec 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 56 186 0 22 Jul 2019
Interpretable Counterfactual Explanations Guided by Prototypes A. V. Looveren Janis Klaise FAtt 55 380 0 03 Jul 2019
Global Explanations of Neural Networks: Mapping the Landscape of Predictions Mark Ibrahim Melissa Louie C. Modarres John Paisley FAtt 50 115 0 06 Feb 2019
Efficient Search for Diverse Coherent Explanations Chris Russell 56 236 0 02 Jan 2019
Actionable Recourse in Linear Classification Berk Ustun Alexander Spangher Yang Liu FaML 90 545 0 18 Sep 2018
Avoiding Latent Variable Collapse With Generative Skip Models Adji Bousso Dieng Yoon Kim Alexander M. Rush David M. Blei DRL 43 174 0 12 Jul 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 96 587 0 21 Feb 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 89 281 0 10 Jan 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 88 2,332 0 01 Nov 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 690 21,613 0 22 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 141 3,848 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 147 5,920 0 04 Mar 2017
Tutorial on Variational Autoencoders Carl Doersch BDL DRL 87 1,736 0 19 Jun 2016
Control of Memory, Active Perception, and Action in Minecraft Michael T. Lash Valliappa Chockalingam Ashwin Balakrishnan Honglak Lee 42 27 0 30 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 746 16,828 0 16 Feb 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 198 4,748 0 04 Jan 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 270 4,143 0 21 May 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 201 18,922 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 204 14,831 1 21 Dec 2013