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Learning Model-Agnostic Counterfactual Explanations for Tabular Data

Learning Model-Agnostic Counterfactual Explanations for Tabular Data

21 October 2019
Martin Pawelczyk
Johannes Haug
Klaus Broelemann
Gjergji Kasneci
    OOD
    CML
ArXivPDFHTML

Papers citing "Learning Model-Agnostic Counterfactual Explanations for Tabular Data"

40 / 40 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
Graph Counterfactual Explainable AI via Latent Space Traversal
Graph Counterfactual Explainable AI via Latent Space Traversal
Andreas Abildtrup Hansen
Paraskevas Pegios
Anna Calissano
Aasa Feragen
OOD
BDL
AAML
83
0
0
15 Jan 2025
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit
Junyu Cao
Ruijiang Gao
Esmaeil Keyvanshokooh
37
1
0
18 Oct 2024
Enhancing Counterfactual Image Generation Using Mahalanobis Distance
  with Distribution Preferences in Feature Space
Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space
Yukai Zhang
Ao Xu
Zihao Li
Tieru Wu
42
1
0
31 May 2024
Counterfactual Metarules for Local and Global Recourse
Counterfactual Metarules for Local and Global Recourse
Tom Bewley
Salim I. Amoukou
Saumitra Mishra
Daniele Magazzeni
Manuela Veloso
42
1
0
29 May 2024
Federated Behavioural Planes: Explaining the Evolution of Client
  Behaviour in Federated Learning
Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning
Dario Fenoglio
Gabriele Dominici
Pietro Barbiero
Alberto Tonda
M. Gjoreski
Marc Langheinrich
FedML
31
0
0
24 May 2024
CountARFactuals -- Generating plausible model-agnostic counterfactual
  explanations with adversarial random forests
CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests
Susanne Dandl
Kristin Blesch
Timo Freiesleben
Gunnar Konig
Jan Kapar
B. Bischl
Marvin N. Wright
AAML
32
5
0
04 Apr 2024
Generating Likely Counterfactuals Using Sum-Product Networks
Generating Likely Counterfactuals Using Sum-Product Networks
Jiri Nemecek
Tomás Pevný
Jakub Marecek
TPM
76
0
0
25 Jan 2024
Distributional Counterfactual Explanations With Optimal Transport
Distributional Counterfactual Explanations With Optimal Transport
Lei You
Lele Cao
Mattias Nilsson
Bo Zhao
Lei Lei
OT
OffRL
20
1
0
23 Jan 2024
The future of human-centric eXplainable Artificial Intelligence (XAI) is
  not post-hoc explanations
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations
Vinitra Swamy
Jibril Frej
Tanja Kaser
29
14
0
01 Jul 2023
Navigating Explanatory Multiverse Through Counterfactual Path Geometry
Navigating Explanatory Multiverse Through Counterfactual Path Geometry
Kacper Sokol
E. Small
Yueqing Xuan
32
5
0
05 Jun 2023
Algorithmic Recourse with Missing Values
Algorithmic Recourse with Missing Values
Kentaro Kanamori
Takuya Takagi
Ken Kobayashi
Yuichi Ike
28
2
0
28 Apr 2023
Generating robust counterfactual explanations
Generating robust counterfactual explanations
Victor Guyomard
Franccoise Fessant
Thomas Guyet
Tassadit Bouadi
Alexandre Termier
35
10
0
24 Apr 2023
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for
  Tabular Data using Normalizing Flows
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows
Tri Dung Duong
Qian Li
Guandong Xu
OOD
34
7
0
26 Mar 2023
Understanding User Preferences in Explainable Artificial Intelligence: A
  Survey and a Mapping Function Proposal
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal
M. Hashemi
Ali Darejeh
Francisco Cruz
40
3
0
07 Feb 2023
CEnt: An Entropy-based Model-agnostic Explainability Framework to
  Contrast Classifiers' Decisions
CEnt: An Entropy-based Model-agnostic Explainability Framework to Contrast Classifiers' Decisions
Julia El Zini
Mohamad Mansour
M. Awad
21
1
0
19 Jan 2023
On Root Cause Localization and Anomaly Mitigation through Causal
  Inference
On Root Cause Localization and Anomaly Mitigation through Causal Inference
Xiao Han
Lu Zhang
Yongkai Wu
Shuhan Yuan
26
7
0
08 Dec 2022
Decomposing Counterfactual Explanations for Consequential Decision
  Making
Decomposing Counterfactual Explanations for Consequential Decision Making
Martin Pawelczyk
Lea Tiyavorabun
Gjergji Kasneci
CML
14
1
0
03 Nov 2022
Towards Explaining Distribution Shifts
Towards Explaining Distribution Shifts
Sean Kulinski
David I. Inouye
OffRL
FAtt
35
24
0
19 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs
CLEAR: Generative Counterfactual Explanations on Graphs
Jing Ma
Ruocheng Guo
Saumitra Mishra
Aidong Zhang
Jundong Li
CML
OOD
30
53
0
16 Oct 2022
Language Models are Realistic Tabular Data Generators
Language Models are Realistic Tabular Data Generators
V. Borisov
Kathrin Seßler
Tobias Leemann
Martin Pawelczyk
Gjergji Kasneci
LMTD
22
223
0
12 Oct 2022
Local and Regional Counterfactual Rules: Summarized and Robust Recourses
Local and Regional Counterfactual Rules: Summarized and Robust Recourses
Salim I. Amoukou
Nicolas Brunel
26
0
0
29 Sep 2022
Differentially Private Counterfactuals via Functional Mechanism
Differentially Private Counterfactuals via Functional Mechanism
Fan Yang
Qizhang Feng
Kaixiong Zhou
Jiahao Chen
Xia Hu
24
8
0
04 Aug 2022
Evaluating the Explainers: Black-Box Explainable Machine Learning for
  Student Success Prediction in MOOCs
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs
Vinitra Swamy
Bahar Radmehr
Natasa Krco
Mirko Marras
Tanja Kaser
FAtt
ELM
11
39
0
01 Jul 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic
  Models
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models
Xiaoting Shao
Kristian Kersting
BDL
22
1
0
16 May 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between
  Costs and Robustness in Algorithmic Recourse
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
Martin Pawelczyk
Teresa Datta
Johannes van-den-Heuvel
Gjergji Kasneci
Himabindu Lakkaraju
19
38
0
13 Mar 2022
Counterfactual Explanations via Latent Space Projection and
  Interpolation
Counterfactual Explanations via Latent Space Projection and Interpolation
Brian Barr
Matthew R. Harrington
Samuel Sharpe
Capital One
BDL
28
10
0
02 Dec 2021
A Survey on the Robustness of Feature Importance and Counterfactual
  Explanations
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
Saumitra Mishra
Sanghamitra Dutta
Jason Long
Daniele Magazzeni
AAML
9
58
0
30 Oct 2021
On Quantitative Evaluations of Counterfactuals
On Quantitative Evaluations of Counterfactuals
Frederik Hvilshoj
Alexandros Iosifidis
Ira Assent
19
10
0
30 Oct 2021
Counterfactual Shapley Additive Explanations
Counterfactual Shapley Additive Explanations
Emanuele Albini
Jason Long
Danial Dervovic
Daniele Magazzeni
26
49
0
27 Oct 2021
Deep Neural Networks and Tabular Data: A Survey
Deep Neural Networks and Tabular Data: A Survey
V. Borisov
Tobias Leemann
Kathrin Seßler
Johannes Haug
Martin Pawelczyk
Gjergji Kasneci
LMTD
27
646
0
05 Oct 2021
Counterfactual Explanations for Arbitrary Regression Models
Counterfactual Explanations for Arbitrary Regression Models
Thomas Spooner
Danial Dervovic
Jason Long
Jon Shepard
Jiahao Chen
Daniele Magazzeni
19
26
0
29 Jun 2021
Exploring Counterfactual Explanations Through the Lens of Adversarial
  Examples: A Theoretical and Empirical Analysis
Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis
Martin Pawelczyk
Chirag Agarwal
Shalmali Joshi
Sohini Upadhyay
Himabindu Lakkaraju
AAML
24
51
0
18 Jun 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable
  Explanations
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations
Pau Rodríguez López
Massimo Caccia
Alexandre Lacoste
L. Zamparo
I. Laradji
Laurent Charlin
David Vazquez
AAML
31
55
0
18 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics
Interpretable Machine Learning: Moving From Mythos to Diagnostics
Valerie Chen
Jeffrey Li
Joon Sik Kim
Gregory Plumb
Ameet Talwalkar
32
29
0
10 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence:
  Theory, Algorithms, and Applications
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
Yu-Liang Chou
Catarina Moreira
P. Bruza
Chun Ouyang
Joaquim A. Jorge
CML
44
176
0
07 Mar 2021
Beyond Individualized Recourse: Interpretable and Interactive Summaries
  of Actionable Recourses
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
Kaivalya Rawal
Himabindu Lakkaraju
27
11
0
15 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and
  Adversarial Examples
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples
Timo Freiesleben
GAN
33
62
0
11 Sep 2020
Model extraction from counterfactual explanations
Model extraction from counterfactual explanations
Ulrich Aivodji
Alexandre Bolot
Sébastien Gambs
MIACV
MLAU
27
51
0
03 Sep 2020
Issues with post-hoc counterfactual explanations: a discussion
Issues with post-hoc counterfactual explanations: a discussion
Thibault Laugel
Marie-Jeanne Lesot
Christophe Marsala
Marcin Detyniecki
CML
104
44
0
11 Jun 2019
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