Charles ASSAAD

Responsibilities

Junior Professor & Inserm Chair

Selected publications

2025:

• Simon Ferreira and Charles K. Assaad. Identifying Macro Causal Effects in C-DMGs over DMGs.In the Thirty-Ninth Annual Conference on Neural Information Processing Systems (Neurips).
• Simon Ferreira and Charles K. Assaad. Identifying Macro Causal Effects in C-DMGs over ADMGs.In Transactions on Machine Learning Research.
• Charles K. Assaad. Towards identifiability of micro total effects in summary causal graphs withlatent confounding: extension of the front-door criterion. In Transactions on Machine Learning Research.
• Charles K. Assaad. Causal reasoning in difference graphs. In the 4th Conference on Causal Learning and Reasoning (CLeaR), (selected for an oral presentation).
• Simon Ferreira and Charles K. Assaad. Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding. In the 39th AAAI Conference on Artificial Intelligence (AAAI), (selected for an oral presentation).
• Benjamin Glemain, Charles K. Assaad, Walid Ghosn, Paul Moulaire, Xavier de Lamballerie, Marie Zins, Gianluca Severi, Mathilde Touvier, Jean-François Deleuze, SAPRIS-SERO Study Group, Nathanael Lapidus, Fabrice Carrat. Revisiting the link between COVID-19 incidence and infection fatality rate during the first pandemic wave. In Scientific Reports.

2024:

• Charles K. Assaad, Emilie Devijver, Eric Gaussier, Gregor Gössler, and Anouar Meynaoui. Identifi- ability of total effects from abstractions of time series causal graphs. In the 40th Conference on Uncertainty in Artificial Intelligence (UAI).
• Lei Zan, Charles K. Assaad, Emilie Devijver, Eric Gaussier, and Ali Aït-Bachir. On the fly detection of root causes from observed data with application to IT systems. In the Conference on Information and Knowledge Management (CIKM).
• Daria Bystrova, Charles K. Assaad, Julyan Arbel, Emilie Devijver, Eric Gaussier, and Wilfried Thuiller. Hybrids of constraint-based and noise-based algorithms for discovering summary causal graphs from time series. In Transactions on Machine Learning Research.
• Simon Ferreira and Charles K. Assaad. Identifiability of direct effects from summary causal graphs. In the 38th AAAI Conference on Artificial Intelligence (AAAI).

2023:

• Charles K. Assaad, Imad Ez-zejjari, and Lei Zan. Root cause identification for collective anomalies in time series given an acyclic summary causal graph with loops. In the 26th International Conference on Artificial Intelligence and Statistics (AISTATS).
• Charles K. Assaad, Emilie Devijver, and Eric Gaussier. Survey and evaluation of causal discovery methods for time series (Extended Abstract). In the 32nd International Joint Conference on Artificial Intelligence (IJCAI).