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Generating Interpretable Counterfactual Explanations By Implicit
  Minimisation of Epistemic and Aleatoric Uncertainties

Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties

16 March 2021
Lisa Schut
Oscar Key
R. McGrath
Luca Costabello
Bogdan Sacaleanu
Medb Corcoran
Y. Gal
    CML
ArXivPDFHTML

Papers citing "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"

15 / 15 papers shown
Title
From Search To Sampling: Generative Models For Robust Algorithmic Recourse
From Search To Sampling: Generative Models For Robust Algorithmic Recourse
Prateek Garg
Lokesh Nagalapatti
Sunita Sarawagi
31
0
0
12 May 2025
Global Counterfactual Directions
Global Counterfactual Directions
Bartlomiej Sobieski
P. Biecek
DiffM
58
5
0
18 Apr 2024
Endogenous Macrodynamics in Algorithmic Recourse
Endogenous Macrodynamics in Algorithmic Recourse
Patrick Altmeyer
Giovan Angela
Aleksander Buszydlik
Karol Dobiczek
A. V. Deursen
Cynthia C. S. Liem
29
7
0
16 Aug 2023
Explaining Black-Box Models through Counterfactuals
Explaining Black-Box Models through Counterfactuals
Patrick Altmeyer
A. V. Deursen
Cynthia C. S. Liem
CML
LRM
37
2
0
14 Aug 2023
Counterfactual Explanations for Misclassified Images: How Human and
  Machine Explanations Differ
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ
Eoin Delaney
A. Pakrashi
Derek Greene
Markt. Keane
35
15
0
16 Dec 2022
Clarity: an improved gradient method for producing quality visual
  counterfactual explanations
Clarity: an improved gradient method for producing quality visual counterfactual explanations
Claire Theobald
Frédéric Pennerath
Brieuc Conan-Guez
Miguel Couceiro
Amedeo Napoli
BDL
38
0
0
22 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision
  Making
Decomposing Counterfactual Explanations for Consequential Decision Making
Martin Pawelczyk
Lea Tiyavorabun
Gjergji Kasneci
CML
21
1
0
03 Nov 2022
Diffusion Visual Counterfactual Explanations
Diffusion Visual Counterfactual Explanations
Maximilian Augustin
Valentyn Boreiko
Francesco Croce
Matthias Hein
DiffM
BDL
32
68
0
21 Oct 2022
What is Flagged in Uncertainty Quantification? Latent Density Models for
  Uncertainty Categorization
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization
Hao Sun
B. V. Breugel
Jonathan Crabbé
Nabeel Seedat
M. Schaar
26
4
0
11 Jul 2022
Sparse Visual Counterfactual Explanations in Image Space
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
Diffusion Models for Counterfactual Explanations
Diffusion Models for Counterfactual Explanations
Guillaume Jeanneret
Loïc Simon
F. Jurie
DiffM
32
55
0
29 Mar 2022
Diffusion Causal Models for Counterfactual Estimation
Diffusion Causal Models for Counterfactual Estimation
Pedro Sanchez
Sotirios A. Tsaftaris
DiffM
BDL
35
69
0
21 Feb 2022
On Quantitative Evaluations of Counterfactuals
On Quantitative Evaluations of Counterfactuals
Frederik Hvilshoj
Alexandros Iosifidis
Ira Assent
19
10
0
30 Oct 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,661
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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