Charles K. Assaad

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

2023

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

[BibT_eX]

[DOI]

CoRR, 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]