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Books and Theses
- 2021
[b1]Charles K. Assaad:
Causal Discovery between time series. (Découvertes de relations causales entreséries temporelles). Grenoble Alpes University, France, 2021
Journal Articles
- 2024
- [j4]Daria Bystrova, Charles K. Assaad, Julyan Arbel, Emilie Devijver, Éric Gaussier, Wilfried Thuiller:
Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms. Trans. Mach. Learn. Res. 2024 (2024) - 2022
- [j3]Charles K. Assaad
, Emilie Devijver, Éric Gaussier:
Entropy-Based Discovery of Summary Causal Graphs in Time Series. Entropy 24(8): 1156 (2022) - [j2]Lei Zan, Anouar Meynaoui, Charles K. Assaad, Emilie Devijver, Éric Gaussier:
A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test. Entropy 24(9): 1234 (2022) - [j1]Charles K. Assaad, Emilie Devijver, Éric Gaussier:
Survey and Evaluation of Causal Discovery Methods for Time Series. J. Artif. Intell. Res. 73: 767-819 (2022)
Conference and Workshop Papers
- 2024
- [c7]Simon Ferreira, Charles K. Assaad:
Identifiability of Direct Effects from Summary Causal Graphs. AAAI 2024: 20387-20394 - [c6]Lei Zan, Charles K. Assaad, Emilie Devijver, Éric Gaussier, Ali Aït-Bachir:
On the Fly Detection of Root Causes from Observed Data with Application to IT Systems. CIKM 2024: 5062-5069 - 2023
- [c5]Charles K. Assaad, Imad Ez-zejjari, Lei Zan:
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops. AISTATS 2023: 8395-8404 - [c4]Charles K. Assaad, Emilie Devijver, Éric Gaussier:
Survey and Evaluation of Causal Discovery Methods for Time Series (Extended Abstract). IJCAI 2023: 6839-6844 - 2022
- [c3]Charles K. Assaad, Emilie Devijver, Éric Gaussier:
Discovery of extended summary graphs in time series. UAI 2022: 96-106 - 2021
- [c2]Charles K. Assaad, Emilie Devijver, Éric Gaussier, Ali Aït-Bachir:
A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series. ECML/PKDD (1) 2021: 453-468 - 2019
- [c1]Charles K. Assaad, Emilie Devijver, Éric Gaussier, Ali Aït-Bachir:
Scaling Causal Inference in Additive Noise Models. CD@KDD 2019: 22-33
Informal and Other Publications
- 2024
- [i9]Lei Zan, Charles K. Assaad, Emilie Devijver, Éric Gaussier:
On the Fly Detection of Root Causes from Observed Data with Application to IT Systems. CoRR abs/2402.06500 (2024) - [i8]Charles K. Assaad:
Toward identifiability of total effects in summary causal graphs with latent confounders: an extension of the front-door criterion. CoRR abs/2406.05805 (2024) - [i7]Simon Ferreira, Charles K. Assaad:
Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding. CoRR abs/2407.07934 (2024) - 2023
- [i6]Charles K. Assaad, Imad Ez-zejjari, Lei Zan:
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops. CoRR abs/2303.04038 (2023) - [i5]Charles K. Assaad, Daria Bystrova, Julyan Arbel, Emilie Devijver, Éric Gaussier, Wilfried Thuiller:
Hybrids of Constraint-based and Noise-based Algorithms for Causal Discovery from Time Series. CoRR abs/2306.08765 (2023) - [i4]Simon Ferreira, Charles K. Assaad:
Identifiability of direct effects from summary causal graphs. CoRR abs/2306.16958 (2023) - [i3]Ali Aït-Bachir, Charles K. Assaad, Christophe de Bignicourt, Emilie Devijver, Simon Ferreira, Éric Gaussier, Hosein Mohanna, Lei Zan:
Case Studies of Causal Discovery from IT Monitoring Time Series. CoRR abs/2307.15678 (2023) - [i2]Charles K. Assaad, Emilie Devijver, Éric Gaussier, Gregor Gössler, Anouar Meynaoui:
Identifiability of total effects from abstractions of time series causal graphs. CoRR abs/2310.14691 (2023) - 2022
- [i1]Charles K. Assaad, Emilie Devijver, Éric Gaussier:
Inferring extended summary causal graphs from observational time series. CoRR abs/2205.09422 (2022)
Coauthor Index
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