Disentangling Influence: Using Disentangled Representations to Audit Model Predictions

20 June 2019

Papers citing "Disentangling Influence: Using Disentangled Representations to Audit Model Predictions"

8 / 8 papers shown

Title
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 50 0 0 29 Oct 2024
Decomposing Counterfactual Explanations for Consequential Decision Making Martin Pawelczyk Lea Tiyavorabun Gjergji Kasneci CML 31 1 0 03 Nov 2022
Marrying Fairness and Explainability in Supervised Learning Przemyslaw A. Grabowicz Nicholas Perello Aarshee Mishra FaML 51 43 0 06 Apr 2022
Learning Disentangled Representations in the Imaging Domain Xiao Liu Pedro Sanchez Spyridon Thermos Alison Q. OÑeil Sotirios A. Tsaftaris OOD DRL 32 71 0 26 Aug 2021
Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs Mohammad Malekzadeh Anastasia Borovykh Deniz Gündüz MIACV 29 42 0 25 May 2021
Privacy-preserving Voice Analysis via Disentangled Representations Ranya Aloufi Hamed Haddadi David E. Boyle DRL 31 58 0 29 Jul 2020
Predictive Multiplicity in Classification Charles Marx Flavio du Pin Calmon Berk Ustun 36 136 0 14 Sep 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 236 676 0 17 Feb 2018