Charles K. Assaad

CoRR, June, 2025

Identifiability by common backdoor in summary causal graphs of time series.

[BibT_eX]

[DOI]

CoRR, June, 2025

Local Markov Equivalence and Local Causal Discovery for Identifying Controlled Direct Effects.

[BibT_eX]

[DOI]

Timothée Loranchet

CoRR, May, 2025

Identifying Macro Causal Effects in C-DMGs.

[BibT_eX]

[DOI]

CoRR, April, 2025

Identifying Macro Causal Effects in a C-DMG over ADMGs.

[BibT_eX]

[DOI]

Simon Matthieu Ferreira

Trans. Mach. Learn. Res., 2025

Towards identifiability of micro total effects in summary causal graphs with latent confounding: extension of the front-door criterion.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2025

Causal reasoning in difference graphs.

[BibT_eX]

[DOI]

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding.

[BibT_eX]

[DOI]

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Discovering maximally consistent distribution of causal tournaments with Large Language Models.

[BibT_eX]

[DOI]

Federico Baldo

CoRR, 2024

Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs.

[BibT_eX]

[DOI]

CoRR, 2024

Toward identifiability of total effects in summary causal graphs with latent confounders: an extension of the front-door criterion.

[BibT_eX]

[DOI]

CoRR, 2024

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems.

[BibT_eX]

[DOI]

CoRR, 2024

Identifiability of total effects from abstractions of time series causal graphs.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2024

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Identifiability of Direct Effects from Summary Causal Graphs.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Case Studies of Causal Discovery from IT Monitoring Time Series.

[BibT_eX]

[DOI]

Ali Aït-Bachir

Christophe de Bignicourt

CoRR, 2023

Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series.

[BibT_eX]

[DOI]

CoRR, 2023

Survey and Evaluation of Causal Discovery Methods for Time Series (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops.

[BibT_eX]

[DOI]

Imad Ez-zejjari

Lei Zan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Survey and Evaluation of Causal Discovery Methods for Time Series.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2022

A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test.

[BibT_eX]

[DOI]

Entropy, 2022

Entropy-Based Discovery of Summary Causal Graphs in Time Series.

[BibT_eX]

[DOI]

Entropy, 2022

Inferring extended summary causal graphs from observational time series.

[BibT_eX]

[DOI]

CoRR, 2022

Discovery of extended summary graphs in time series.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Causal Discovery between time series. (Découvertes de relations causales entreséries temporelles).

[BibT_eX]

[DOI]