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2103.08951
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Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
16 March 2021
Lisa Schut
Oscar Key
R. McGrath
Luca Costabello
Bogdan Sacaleanu
Medb Corcoran
Y. Gal
CML
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Papers citing
"Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
39 / 39 papers shown
CONFEX: Uncertainty-Aware Counterfactual Explanations with Conformal Guarantees
Aman Bilkhoo
Mehran Hosseini
Milad Kazemi
Nicola Paoletti
218
0
0
22 Oct 2025
Counterfactual Visual Explanation via Causally-Guided Adversarial Steering
Yiran Qiao
Disheng Liu
Yiren Lu
Yu Yin
Mengnan Du
Jing Ma
GAN
CML
AAML
326
1
0
14 Jul 2025
Diffusion Counterfactual Generation with Semantic Abduction
Rajat Rasal
Avinash Kori
Fabio De Sousa Ribeiro
Tian Xia
Ben Glocker
DiffM
315
4
0
09 Jun 2025
From Search To Sampling: Generative Models For Robust Algorithmic Recourse
International Conference on Learning Representations (ICLR), 2025
Prateek Garg
Lokesh Nagalapatti
Sunita Sarawagi
480
4
0
12 May 2025
GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals
Asiful Arefeen
Saman Khamesian
Maria Adela Grando
Bithika Thompson
Hassan Ghasemzadeh
271
4
0
14 Apr 2025
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification
Jonas Teufel
Annika Leinweber
Pascal Friederich
465
4
0
03 Apr 2025
All You Need for Counterfactual Explainability Is Principled and Reliable Estimate of Aleatoric and Epistemic Uncertainty
Kacper Sokol
Eyke Hüllermeier
470
4
0
24 Feb 2025
Rethinking Visual Counterfactual Explanations Through Region Constraint
International Conference on Learning Representations (ICLR), 2024
Bartlomiej Sobieski
Jakub Grzywaczewski
Bartlomiej Sadlej
Matthew Tivnan
P. Biecek
CML
249
15
0
16 Oct 2024
Global Counterfactual Directions
Bartlomiej Sobieski
P. Biecek
DiffM
629
14
0
18 Apr 2024
Generating Feasible and Plausible Counterfactual Explanations for Outcome Prediction of Business Processes
IEEE Transactions on Services Computing (IEEE TSC), 2024
Alexander Stevens
Chun Ouyang
Johannes De Smedt
Catarina Moreira
CML
242
4
0
14 Mar 2024
Natural Counterfactuals With Necessary Backtracking
Guang-Yuan Hao
Jiji Zhang
Erdun Gao
Hao Wang
Kun Zhang
260
1
0
02 Feb 2024
Causal Generative Explainers using Counterfactual Inference: A Case Study on the Morpho-MNIST Dataset
Pattern Analysis and Applications (PAA), 2024
William Taylor-Melanson
Zahra Sadeghi
Stan Matwin
CML
229
11
0
21 Jan 2024
Faithful Model Explanations through Energy-Constrained Conformal Counterfactuals
Patrick Altmeyer
Mojtaba Farmanbar
A. V. Deursen
Cynthia C. S. Liem
212
7
0
17 Dec 2023
Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
Asiful Arefeen
Hassan Ghasemzadeh
260
6
0
02 Oct 2023
Endogenous Macrodynamics in Algorithmic Recourse
Patrick Altmeyer
Giovan Angela
Aleksander Buszydlik
Karol Dobiczek
A. V. Deursen
Cynthia C. S. Liem
246
9
0
16 Aug 2023
Explaining Black-Box Models through Counterfactuals
JuliaCon Proceedings (JuliaCon), 2023
Patrick Altmeyer
A. V. Deursen
Cynthia C. S. Liem
CML
LRM
255
4
0
14 Aug 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models
International Conference on Machine Learning (ICML), 2023
Fabio De Sousa Ribeiro
Tian Xia
M. Monteiro
Nick Pawlowski
Ben Glocker
DiffM
301
68
0
27 Jun 2023
Adversarial Counterfactual Visual Explanations
Computer Vision and Pattern Recognition (CVPR), 2023
Guillaume Jeanneret
Loïc Simon
F. Jurie
DiffM
362
53
0
17 Mar 2023
Two-step counterfactual generation for OOD examples
Nawid Keshtmand
Raúl Santos-Rodríguez
J. Lawry
OODD
CML
170
0
0
10 Feb 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ
Artificial Intelligence (AI), 2022
Eoin Delaney
A. Pakrashi
Derek Greene
Markt. Keane
330
27
0
16 Dec 2022
Clarity: an improved gradient method for producing quality visual counterfactual explanations
Claire Theobald
Frédéric Pennerath
Brieuc Conan-Guez
Miguel Couceiro
Amedeo Napoli
BDL
298
1
0
22 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision Making
Martin Pawelczyk
Lea Tiyavorabun
Gjergji Kasneci
CML
197
1
0
03 Nov 2022
Diffusion Visual Counterfactual Explanations
Neural Information Processing Systems (NeurIPS), 2022
Maximilian Augustin
Valentyn Boreiko
Francesco Croce
Matthias Hein
DiffM
BDL
263
106
0
21 Oct 2022
Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Julia El Zini
M. Awad
AAML
238
2
0
17 Oct 2022
What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization
Neural Information Processing Systems (NeurIPS), 2022
Hao Sun
B. V. Breugel
Jonathan Crabbé
Nabeel Seedat
M. Schaar
286
5
0
11 Jul 2022
Diffeomorphic Counterfactuals with Generative Models
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Ann-Kathrin Dombrowski
Jan E. Gerken
Klaus-Robert Muller
Pan Kessel
DiffM
BDL
394
26
0
10 Jun 2022
Sparse Visual Counterfactual Explanations in Image Space
German Conference on Pattern Recognition (GCPR), 2022
Valentyn Boreiko
Maximilian Augustin
Francesco Croce
Philipp Berens
Matthias Hein
BDL
CML
426
34
0
16 May 2022
Diffusion Models for Counterfactual Explanations
Asian Conference on Computer Vision (ACCV), 2022
Guillaume Jeanneret
Loïc Simon
F. Jurie
DiffM
426
82
0
29 Mar 2022
Diffusion Causal Models for Counterfactual Estimation
CLEaR (CLEaR), 2022
Pedro Sanchez
Sotirios A. Tsaftaris
DiffM
BDL
380
106
0
21 Feb 2022
DeDUCE: Generating Counterfactual Explanations Efficiently
Benedikt Höltgen
Lisa Schut
J. Brauner
Y. Gal
CML
192
6
0
29 Nov 2021
Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model
Jing Zhang
Yuchao Dai
Mehrtash Harandi
Yiran Zhong
Nick Barnes
Leonid Sigal
UQCV
238
1
0
22 Nov 2021
On Quantitative Evaluations of Counterfactuals
Frederik Hvilshoj
Alexandros Iosifidis
Ira Assent
254
11
0
30 Oct 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations
Hangzhi Guo
T. Nguyen
A. Yadav
OffRL
299
24
0
15 Sep 2021
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
Martin Pawelczyk
Sascha Bielawski
J. V. D. Heuvel
Tobias Richter
Gjergji Kasneci
CML
317
124
0
02 Aug 2021
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions
Eoin Delaney
Derek Greene
Mark T. Keane
249
30
0
20 Jul 2021
Attribution of Predictive Uncertainties in Classification Models
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Iker Perez
Piotr Skalski
Alec E. Barns-Graham
Jason Wong
David Sutton
UQCV
362
8
0
19 Jul 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
653
183
0
05 Feb 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
ACM Computing Surveys (ACM CSUR), 2020
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
812
281
0
20 Oct 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCV
BDL
983
546
0
17 Jun 2020
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