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Cited By
Counterfactual Explanations for Arbitrary Regression Models
29 June 2021
Thomas Spooner
Danial Dervovic
Jason Long
Jon Shepard
Jiahao Chen
Daniele Magazzeni
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Papers citing
"Counterfactual Explanations for Arbitrary Regression Models"
19 / 19 papers shown
ACE: Adapting sampling for Counterfactual Explanations
Margarita A. Guerrero
Cristian R. Rojas
137
1
0
30 Sep 2025
Diffusion Counterfactuals for Image Regressors
Trung Duc Ha
Sidney Bender
DiffM
439
4
0
26 Mar 2025
Relevance-aware Algorithmic Recourse
Dongwhi Kim
Nuno Moniz
313
0
0
29 May 2024
Counterfactual Metarules for Local and Global Recourse
Tom Bewley
Salim I. Amoukou
Saumitra Mishra
Daniele Magazzeni
Manuela Veloso
347
4
0
29 May 2024
Counterfactual Explanations for Deep Learning-Based Traffic Forecasting
Rushan Wang
Yanan Xin
Yatao Zhang
Fernando Pérez-Cruz
Martin Raubal
AI4TS
366
10
0
01 May 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
Counterfactual Explanation for Regression via Disentanglement in Latent Space
Xuan Zhao
Klaus Broelemann
Gjergji Kasneci
OOD
CML
BDL
345
3
0
14 Nov 2023
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023
Emanuele Albini
Sanjay Kariyappa
Saumitra Mishra
Danial Dervovic
Daniele Magazzeni
FAtt
312
5
0
13 Jul 2023
Unveiling the Potential of Counterfactuals Explanations in Employability
Raphael Mazzine Barbosa de Oliveira
S. Goethals
Dieter Brughmans
David Martens
323
3
0
17 May 2023
Counterfactual Explanations of Neural Network-Generated Response Curves
IEEE International Joint Conference on Neural Network (IJCNN), 2023
Giorgio Morales
John W. Sheppard
255
1
0
08 Apr 2023
On the Privacy Risks of Algorithmic Recourse
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Martin Pawelczyk
Himabindu Lakkaraju
Seth Neel
197
39
0
10 Nov 2022
Decomposing Counterfactual Explanations for Consequential Decision Making
Martin Pawelczyk
Lea Tiyavorabun
Gjergji Kasneci
CML
191
1
0
03 Nov 2022
On the Trade-Off between Actionable Explanations and the Right to be Forgotten
International Conference on Learning Representations (ICLR), 2022
Martin Pawelczyk
Tobias Leemann
Asia J. Biega
Gjergji Kasneci
FaML
MU
474
26
0
30 Aug 2022
Robust Counterfactual Explanations for Tree-Based Ensembles
International Conference on Machine Learning (ICML), 2022
Sanghamitra Dutta
Jason Long
Saumitra Mishra
Cecilia Tilli
Daniele Magazzeni
380
71
0
06 Jul 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
International Conference on Learning Representations (ICLR), 2022
Martin Pawelczyk
Teresa Datta
Johannes van-den-Heuvel
Gjergji Kasneci
Himabindu Lakkaraju
494
42
0
13 Mar 2022
Toward Explainable AI for Regression Models
IEEE Signal Processing Magazine (IEEE SPM), 2021
S. Letzgus
Patrick Wagner
Jonas Lederer
Wojciech Samek
Klaus-Robert Muller
G. Montavon
XAI
277
86
0
21 Dec 2021
Counterfactual Shapley Additive Explanations
Emanuele Albini
Jason Long
Danial Dervovic
Daniele Magazzeni
637
69
0
27 Oct 2021
ReLAX: Reinforcement Learning Agent eXplainer for Arbitrary Predictive Models
International Conference on Information and Knowledge Management (CIKM), 2021
Kiran Purohit
Soumili Das
Jia Wang
He Zhu
Santu Rana
Gabriele Tolomei
CML
OffRL
215
44
0
22 Oct 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
796
281
0
20 Oct 2020
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