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1908.03020
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Measurable Counterfactual Local Explanations for Any Classifier
European Conference on Artificial Intelligence (ECAI), 2019
8 August 2019
Adam White
Artur Garcez
FAtt
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Papers citing
"Measurable Counterfactual Local Explanations for Any Classifier"
50 / 57 papers shown
Looking in the mirror: A faithful counterfactual explanation method for interpreting deep image classification models
T. Chowdhury
Vu Minh Hieu Phan
Kewen Liao
Nanyu Dong
Minh-Son To
Anton van den Hengel
Johan Verjans
Zhibin Liao
OOD
199
1
0
20 Sep 2025
An Explainable Gaussian Process Auto-encoder for Tabular Data
Wei Zhang
Brian Barr
John Paisley
CML
203
1
0
31 Aug 2025
Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room
Danial Hooshyar
Gustav Šír
Yeongwook Yang
Eve Kikas
Raija Hamalainen
T. Karkkainen
Dragan Gašević
Roger Azevedo
452
8
0
22 Apr 2025
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods
Danial Hooshyar
Eve Kikas
Yeongwook Yang
Gustav Šír
Raija Hamalainen
T. Karkkainen
Roger Azevedo
483
3
0
01 Apr 2025
Generating Causally Compliant Counterfactual Explanations using ASP
International Conference on Logic Programming (ICLP), 2025
Sopam Dasgupta
CML
306
1
0
13 Feb 2025
CoGS: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta
Joaquín Arias
Elmer Salazar
Gopal Gupta
CML
284
3
0
11 Jul 2024
Identification and Uses of Deep Learning Backbones via Pattern Mining
Michael J. Livanos
Ian Davidson
139
0
0
27 Mar 2024
Introducing User Feedback-based Counterfactual Explanations (UFCE)
M. Nizami
J. Alonso-Moral
Alessandro Bogliolo
CML
219
5
0
26 Feb 2024
Counterfactual Generation with Answer Set Programming
Sopam Dasgupta
Farhad Shakerin
Joaquín Arias
Elmer Salazar
Gopal Gupta
265
1
0
06 Feb 2024
Explainable AI for survival analysis: a median-SHAP approach
Lucile Ter-Minassian
Sahra Ghalebikesabi
Karla Diaz-Ordaz
Chris Holmes
288
4
0
30 Jan 2024
FocusLearn: Fully-Interpretable, High-Performance Modular Neural Networks for Time Series
IEEE International Joint Conference on Neural Network (IJCNN), 2023
Qiqi Su
Christos Kloukinas
Artur dÁvila Garcez
AI4TS
423
9
0
28 Nov 2023
Predicting recovery following stroke: deep learning, multimodal data and feature selection using explainable AI
Adam White
Margarita Saranti
Artur dÁvila Garcez
T. Hope
Cathy J. Price
Howard Bowman
225
19
0
29 Oct 2023
How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?
Zachariah Carmichael
Walter J. Scheirer
FAtt
301
8
0
27 Oct 2023
Counterfactual Explanation Generation with s(CASP)
Sopam Dasgupta
Farhad Shakerin
Joaquín Arias
Elmer Salazar
Gopal Gupta
LRM
313
1
0
23 Oct 2023
Right for the Wrong Reason: Can Interpretable ML Techniques Detect Spurious Correlations?
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
Susu Sun
Lisa M. Koch
Christian F. Baumgartner
342
21
0
23 Jul 2023
BELLA: Black box model Explanations by Local Linear Approximations
N. Radulovic
Nikolaos Perrakis
Fabian M. Suchanek
FAtt
441
1
0
18 May 2023
Very fast, approximate counterfactual explanations for decision forests
AAAI Conference on Artificial Intelligence (AAAI), 2023
Miguel Á. Carreira-Perpiñán
Suryabhan Singh Hada
197
6
0
06 Mar 2023
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals
International Conference on Medical Imaging with Deep Learning (MIDL), 2023
Susu Sun
S. Woerner
Andreas Maier
Lisa M. Koch
Christian F. Baumgartner
FAtt
488
19
0
01 Mar 2023
Explaining Random Forests using Bipolar Argumentation and Markov Networks (Technical Report)
AAAI Conference on Artificial Intelligence (AAAI), 2022
Nico Potyka
Xiang Yin
Francesca Toni
158
18
0
21 Nov 2022
RAGUEL: Recourse-Aware Group Unfairness Elimination
International Conference on Information and Knowledge Management (CIKM), 2022
Aparajita Haldar
Teddy Cunningham
Hakan Ferhatosmanoglu
FaML
185
4
0
30 Aug 2022
Differentially Private Counterfactuals via Functional Mechanism
Fan Yang
Qizhang Feng
Kaixiong Zhou
Jiahao Chen
Helen Zhou
186
16
0
04 Aug 2022
Explanatory causal effects for model agnostic explanations
Jiuyong Li
Ha Xuan Tran
T. Le
Lin Liu
Kui Yu
Jixue Liu
CML
178
1
0
23 Jun 2022
Robust Bayesian Recourse
Conference on Uncertainty in Artificial Intelligence (UAI), 2022
Tuan-Duy H. Nguyen
Ngoc H. Bui
D. Nguyen
Man-Chung Yue
Viet Anh Nguyen
310
17
0
22 Jun 2022
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting
Conference on Fairness, Accountability and Transparency (FAccT), 2022
Ulrike Kuhl
André Artelt
Barbara Hammer
258
29
0
11 May 2022
Let's Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning
Ulrike Kuhl
André Artelt
Barbara Hammer
238
23
0
06 May 2022
Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box
ACM Computing Surveys (ACM CSUR), 2022
Catarina Moreira
Yu-Liang Chou
Chih-Jou Hsieh
Chun Ouyang
Joaquim A. Jorge
João Pereira
CML
461
13
0
04 Mar 2022
Post-discovery Analysis of Anomalous Subsets
I. Mulang'
William Ogallo
G. Tadesse
Aisha Walcott-Bryant
179
1
0
23 Nov 2021
A Practical guide on Explainable AI Techniques applied on Biomedical use case applications
Social Science Research Network (SSRN), 2021
Adrien Bennetot
Ivan Donadello
Ayoub El Qadi
M. Dragoni
Thomas Frossard
...
M. Trocan
Raja Chatila
Andreas Holzinger
Artur Garcez
Natalia Díaz Rodríguez
XAI
235
13
0
13 Nov 2021
Counterfactual Shapley Additive Explanations
Emanuele Albini
Jason Long
Danial Dervovic
Daniele Magazzeni
597
69
0
27 Oct 2021
Accountability in AI: From Principles to Industry-specific Accreditation
AI Communications (AI Commun.), 2021
Christian Percy
S. Dragicevic
Sanjoy Sarkar
Artur Garcez
145
18
0
08 Oct 2021
Counterfactual Instances Explain Little
Adam White
Artur Garcez
CML
243
5
0
20 Sep 2021
Model Explanations via the Axiomatic Causal Lens
Gagan Biradar
Vignesh Viswanathan
Yair Zick
XAI
CML
544
1
0
08 Sep 2021
Harnessing value from data science in business: ensuring explainability and fairness of solutions
Krzysztof Chomiak
Michal Miktus
132
1
0
10 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data
Applied Sciences (AS), 2021
Raphael Mazzine
David Martens
244
37
0
09 Jul 2021
Contrastive Counterfactual Visual Explanations With Overdetermination
Machine-mediated learning (ML), 2021
Adam White
K. Ngan
James Phelan
Saman Sadeghi Afgeh
Kevin Ryan
C. Reyes-Aldasoro
Artur Garcez
275
12
0
28 Jun 2021
On Locality of Local Explanation Models
Sahra Ghalebikesabi
Lucile Ter-Minassian
Karla Diaz-Ordaz
Chris Holmes
FedML
FAtt
206
46
0
24 Jun 2021
Model-Based Counterfactual Synthesizer for Interpretation
Fan Yang
Sahan Suresh Alva
Jiahao Chen
X. Hu
133
36
0
16 Jun 2021
A Framework for Evaluating Post Hoc Feature-Additive Explainers
Zachariah Carmichael
Walter J. Scheirer
FAtt
232
5
0
15 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
386
28
0
07 Jun 2021
An exact counterfactual-example-based approach to tree-ensemble models interpretability
P. Blanchart
181
6
0
31 May 2021
SurvNAM: The machine learning survival model explanation
Neural Networks (NN), 2021
Lev V. Utkin
Egor D. Satyukov
A. Konstantinov
AAML
FAtt
249
38
0
18 Apr 2021
A Study of Automatic Metrics for the Evaluation of Natural Language Explanations
Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2021
Miruna Clinciu
Arash Eshghi
H. Hastie
242
61
0
15 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
Information Fusion (Inf. Fusion), 2021
Yu-Liang Chou
Catarina Moreira
P. Bruza
Chun Ouyang
Joaquim A. Jorge
CML
430
226
0
07 Mar 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
366
170
0
26 Feb 2021
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation
SIGKDD Explorations (SIGKDD Explor.), 2021
Fan Yang
Ninghao Liu
Mengnan Du
X. Hu
OOD
251
18
0
18 Jan 2021
Neurosymbolic AI: The 3rd Wave
Artificial Intelligence Review (AIR), 2020
Artur Garcez
Luís C. Lamb
NAI
449
454
0
10 Dec 2020
Influence-Driven Explanations for Bayesian Network Classifiers
Pacific Rim International Conference on Artificial Intelligence (PRICAI), 2020
Antonio Rago
Emanuele Albini
P. Baroni
Francesca Toni
322
9
0
10 Dec 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
781
279
0
20 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
409
186
0
08 Oct 2020
Counterfactual explanation of machine learning survival models
M. Kovalev
Lev V. Utkin
CML
OffRL
290
24
0
26 Jun 2020
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