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2003.06868
Cited By
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Causality-based Explanation of Classification Outcomes
15 March 2020
Leopoldo Bertossi
Jordan Li
Maximilian Schleich
Dan Suciu
Zografoula Vagena
XAI
CML
FAtt
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Papers citing
"Causality-based Explanation of Classification Outcomes"
30 / 30 papers shown
SHAP Meets Tensor Networks: Provably Tractable Explanations with Parallelism
Reda Marzouk
Shahaf Bassan
Guy Katz
FAtt
312
6
0
24 Oct 2025
Feature Relevancy, Necessity and Usefulness: Complexity and Algorithms
Tomás Capdevielle
Santiago Cifuentes
FAtt
246
1
0
06 May 2025
The Causal-Effect Score in Data Management
CLEaR (CLEaR), 2025
Felipe Azua
Leopoldo Bertossi
CML
450
2
0
04 Feb 2025
On the Tractability of SHAP Explanations under Markovian Distributions
International Conference on Machine Learning (ICML), 2024
Reda Marzouk
C. D. L. Higuera
FAtt
351
13
0
05 May 2024
Automated Discovery of Functional Actual Causes in Complex Environments
Caleb Chuck
Sankaran Vaidyanathan
Stephen Giguere
Amy Zhang
David Jensen
S. Niekum
CML
363
3
0
16 Apr 2024
Causality from Bottom to Top: A Survey
Abraham Itzhak Weinberg
Cristiano Premebida
Diego Resende Faria
CML
312
6
0
17 Mar 2024
The Distributional Uncertainty of the SHAP score in Explainable Machine Learning
European Conference on Artificial Intelligence (ECAI), 2024
Santiago Cifuentes
L. Bertossi
Nina Pardal
S. Abriola
Maria Vanina Martinez
Miguel Romero
TDI
FAtt
323
2
0
23 Jan 2024
Attribution-Scores in Data Management and Explainable Machine Learning
Symposium on Advances in Databases and Information Systems (ADBIS), 2023
Leopoldo Bertossi
XAI
FAtt
CML
258
1
0
31 Jul 2023
Efficient Computation of Shap Explanation Scores for Neural Network Classifiers via Knowledge Compilation
European Conference on Logics in Artificial Intelligence (JELIA), 2023
Leopoldo Bertossi
Jorge E. Leon
FAtt
361
2
0
11 Mar 2023
Attribution-Scores and Causal Counterfactuals as Explanations in Artificial Intelligence
Leopoldo Bertossi
XAI
CML
433
5
0
06 Mar 2023
A Quantum Algorithm for Shapley Value Estimation
International Conference on Quantum Computing and Engineering (QCE), 2023
Iain Burge
Michel Barbeau
Joaquín García
184
3
0
11 Jan 2023
Answer-Set Programs for Repair Updates and Counterfactual Interventions
Leopoldo Bertossi
KELM
AAML
180
0
0
25 Sep 2022
XInsight: eXplainable Data Analysis Through The Lens of Causality
Pingchuan Ma
Rui Ding
Shuai Wang
Shi Han
Dongmei Zhang
CML
493
27
0
26 Jul 2022
Explaining Image Classifiers Using Contrastive Counterfactuals in Generative Latent Spaces
Kamran Alipour
Aditya Lahiri
Ehsan Adeli
Babak Salimi
M. Pazzani
CML
195
7
0
10 Jun 2022
Causal Explanations for Sequential Decision Making Under Uncertainty
Adaptive Agents and Multi-Agent Systems (AAMAS), 2022
Samer B. Nashed
Saaduddin Mahmud
C. V. Goldman
S. Zilberstein
CML
335
4
0
30 May 2022
ExMo: Explainable AI Model using Inverse Frequency Decision Rules
Interacción (IN), 2022
Pradip Mainali
I. Psychoula
F. Petitcolas
213
1
0
20 May 2022
Statistics and Deep Learning-based Hybrid Model for Interpretable Anomaly Detection
Thabang Mathonsi
Terence L van Zyl
207
1
0
25 Feb 2022
Interpretable Data-Based Explanations for Fairness Debugging
Romila Pradhan
Jiongli Zhu
Boris Glavic
Babak Salimi
398
68
0
17 Dec 2021
Reasoning about Counterfactuals and Explanations: Problems, Results and Directions
Leopoldo Bertossi
LRM
193
0
0
25 Aug 2021
Seven challenges for harmonizing explainability requirements
Jiahao Chen
Victor Storchan
287
9
0
11 Aug 2021
Answer-Set Programs for Reasoning about Counterfactual Interventions and Responsibility Scores for Classification
International Conference on Inductive Logic Programming (ILP), 2021
Leopoldo Bertossi
G. Reyes
246
10
0
21 Jul 2021
Score-Based Explanations in Data Management and Machine Learning: An Answer-Set Programming Approach to Counterfactual Analysis
Leopoldo Bertossi
230
4
0
19 Jun 2021
On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results
Journal of machine learning research (JMLR), 2021
Marcelo Arenas
Pablo Barceló
Leopoldo Bertossi
Mikaël Monet
FAtt
325
48
0
16 Apr 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals
Sainyam Galhotra
Romila Pradhan
Babak Salimi
CML
346
121
0
22 Mar 2021
Declarative Approaches to Counterfactual Explanations for Classification
Theory and Practice of Logic Programming (TPLP), 2020
Leopoldo Bertossi
542
17
0
15 Nov 2020
Exathlon: A Benchmark for Explainable Anomaly Detection over Time Series
Proceedings of the VLDB Endowment (PVLDB), 2020
Vincent Jacob
Fei Song
Arnaud Stiegler
Bijan Rad
Y. Diao
Nesime Tatbul
AI4TS
348
93
0
10 Oct 2020
On the Tractability of SHAP Explanations
AAAI Conference on Artificial Intelligence (AAAI), 2020
Karen Ullrich
A. Lykov
Maximilian Schleich
Dan Suciu
FAtt
TDI
438
477
0
18 Sep 2020
The Tractability of SHAP-Score-Based Explanations over Deterministic and Decomposable Boolean Circuits
Marcelo Arenas
Pablo Barceló
Mikaël Monet
FAtt
322
8
0
28 Jul 2020
Score-Based Explanations in Data Management and Machine Learning
Scalable Uncertainty Management (SUM), 2020
Leopoldo Bertossi
FAtt
XAI
286
4
0
24 Jul 2020
An ASP-Based Approach to Counterfactual Explanations for Classification
Leopoldo Bertossi
CML
401
19
0
28 Apr 2020
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