Explaining Data-Driven Decisions made by AI Systems: The Counterfactual
Approach

Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach

21 January 2020

Carlos Fernandez

Papers citing "Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach"

14 / 14 papers shown

Title
ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models Arkadipta De Satya Swaroop Gudipudi Sourab Panchanan M. Desarkar FaML 18 0 0 30 Dec 2022
A General Search-based Framework for Generating Textual Counterfactual Explanations Daniel Gilo Shaul Markovitch LRM 41 0 0 01 Nov 2022
Counterfactual Explanations via Latent Space Projection and Interpolation Brian Barr Matthew R. Harrington Samuel Sharpe Capital One BDL 35 10 0 02 Dec 2021
Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data Yanou Ramon S. Matz R. Farrokhnia David Martens 30 17 0 12 Nov 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 40 33 0 09 Jul 2021
Understanding Consumer Preferences for Explanations Generated by XAI Algorithms Yanou Ramon T. Vermeire Olivier Toubia David Martens Theodoros Evgeniou 34 10 0 06 Jul 2021
To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods E. Amparore Alan Perotti P. Bajardi FAtt 33 68 0 01 Jun 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations Dieter Brughmans Pieter Leyman David Martens 35 63 0 15 Apr 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice David S. Watson Limor Gultchin Ankur Taly Luciano Floridi 22 63 0 27 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 27 146 0 26 Feb 2021
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 26 164 0 20 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 43 62 0 11 Sep 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 27 19 0 26 Jun 2020
ViCE: Visual Counterfactual Explanations for Machine Learning Models Oscar Gomez Steffen Holter Jun Yuan E. Bertini AAML 59 93 0 05 Mar 2020