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1912.03277
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Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers
6 December 2019
Divyat Mahajan
Chenhao Tan
Amit Sharma
OOD
CML
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Papers citing
"Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"
37 / 137 papers shown
Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations
Abubakar Abid
Mert Yuksekgonul
James Zou
CML
199
74
0
24 Jun 2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
Roland S. Zimmermann
Judy Borowski
Robert Geirhos
Matthias Bethge
Thomas S. A. Wallis
Wieland Brendel
FAtt
318
39
0
23 Jun 2021
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects
Julius von Kügelgen
N. Agarwal
Jakob Zeitler
Afsaneh Mastouri
Bernhard Schölkopf
CML
183
3
0
22 Jun 2021
Rational Shapley Values
Conference on Fairness, Accountability and Transparency (FAccT), 2021
David S. Watson
127
27
0
18 Jun 2021
Model-Based Counterfactual Synthesizer for Interpretation
Fan Yang
Sahan Suresh Alva
Jiahao Chen
X. Hu
99
34
0
16 Jun 2021
Counterfactual Explanations for Machine Learning: Challenges Revisited
Sahil Verma
John P Dickerson
Keegan E. Hines
LRM
98
37
0
14 Jun 2021
Counterfactual Explanations as Interventions in Latent Space
Data mining and knowledge discovery (DMKD), 2021
Riccardo Crupi
Alessandro Castelnovo
D. Regoli
Beatriz San Miguel González
CML
174
28
0
14 Jun 2021
Optimal Counterfactual Explanations in Tree Ensembles
International Conference on Machine Learning (ICML), 2021
Axel Parmentier
Thibaut Vidal
195
61
0
11 Jun 2021
Amortized Generation of Sequential Algorithmic Recourses for Black-box Models
AAAI Conference on Artificial Intelligence (AAAI), 2021
Sahil Verma
Keegan E. Hines
John P. Dickerson
313
26
0
07 Jun 2021
Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models
B. La Rosa
Roberto Capobianco
Daniele Nardi
VLM
158
10
0
01 Jun 2021
Explainable Machine Learning with Prior Knowledge: An Overview
Katharina Beckh
Sebastian Müller
Matthias Jakobs
Vanessa Toborek
Hanxiao Tan
Raphael Fischer
Pascal Welke
Sebastian Houben
Laura von Rueden
XAI
285
31
0
21 May 2021
Convex optimization for actionable \& plausible counterfactual explanations
André Artelt
Barbara Hammer
CML
OffRL
145
10
0
17 May 2021
Causality-based Counterfactual Explanation for Classification Models
Knowledge-Based Systems (KBS), 2021
Tri Dung Duong
Qian Li
Guandong Xu
CML
208
5
0
03 May 2021
DA-DGCEx: Ensuring Validity of Deep Guided Counterfactual Explanations With Distribution-Aware Autoencoder Loss
Jokin Labaien
E. Zugasti
Xabier De Carlos
CML
204
4
0
19 Apr 2021
NICE: An Algorithm for Nearest Instance Counterfactual Explanations
Data mining and knowledge discovery (DMKD), 2021
Dieter Brughmans
Pieter Leyman
David Martens
240
82
0
15 Apr 2021
Consequence-aware Sequential Counterfactual Generation
Philip Naumann
Eirini Ntoutsi
OffRL
230
27
0
12 Apr 2021
ECINN: Efficient Counterfactuals from Invertible Neural Networks
British Machine Vision Conference (BMVC), 2021
Frederik Hvilshoj
Alexandros Iosifidis
Ira Assent
BDL
200
31
0
25 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra
Romila Pradhan
Babak Salimi
CML
259
117
0
22 Mar 2021
Towards Robust and Reliable Algorithmic Recourse
Neural Information Processing Systems (NeurIPS), 2021
Sohini Upadhyay
Shalmali Joshi
Himabindu Lakkaraju
256
121
0
26 Feb 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Mark T. Keane
Eoin M. Kenny
Eoin Delaney
Barry Smyth
CML
297
165
0
26 Feb 2021
Conditional Generative Models for Counterfactual Explanations
A. V. Looveren
Janis Klaise
G. Vacanti
Oliver Cobb
CML
133
36
0
25 Jan 2021
Explaining the Black-box Smoothly- A Counterfactual Approach
Junyu Chen
Yong Du
Yufan He
W. Paul Segars
Ye Li
MedIm
FAtt
320
128
0
11 Jan 2021
GeCo: Quality Counterfactual Explanations in Real Time
Proceedings of the VLDB Endowment (PVLDB), 2021
Maximilian Schleich
Zixuan Geng
Yihong Zhang
D. Suciu
295
74
0
05 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour
Ricards Marcinkevics
Julia E. Vogt
XAI
351
133
0
03 Dec 2020
A Survey on the Explainability of Supervised Machine Learning
Journal of Artificial Intelligence Research (JAIR), 2020
Nadia Burkart
Marco F. Huber
FaML
XAI
253
893
0
16 Nov 2020
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End
R. Mothilal
Divyat Mahajan
Chenhao Tan
Amit Sharma
FAtt
CML
455
121
0
10 Nov 2020
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
703
247
0
20 Oct 2020
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
FaML
650
92
0
13 Oct 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations
Andrea Ferrario
M. Loi
177
5
0
09 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
346
184
0
08 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Minds and Machines (MM), 2020
Timo Freiesleben
GAN
500
71
0
11 Sep 2020
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning
AAAI Conference on Artificial Intelligence (AAAI), 2020
Eoin M. Kenny
Mark T. Keane
247
114
0
10 Sep 2020
On Counterfactual Explanations under Predictive Multiplicity
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Martin Pawelczyk
Klaus Broelemann
Gjergji Kasneci
230
97
0
23 Jun 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
Neural Information Processing Systems (NeurIPS), 2020
Amir-Hossein Karimi
Julius von Kügelgen
Bernhard Schölkopf
Isabel Valera
CML
415
190
0
11 Jun 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Conference on Fairness, Accountability and Transparency (FAccT), 2020
Amir-Hossein Karimi
Bernhard Schölkopf
Isabel Valera
CML
536
391
0
14 Feb 2020
Two Causal Principles for Improving Visual Dialog
Computer Vision and Pattern Recognition (CVPR), 2019
Jiaxin Qi
Yulei Niu
Jianqiang Huang
Hanwang Zhang
CML
590
159
0
24 Nov 2019
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability
Neural Information Processing Systems (NeurIPS), 2019
Christopher Frye
C. Rowat
Ilya Feige
330
212
0
14 Oct 2019
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