-
S. Ferreira and C. K. Assaad. Average controlled and average natural micro direct effects in summary causal graphs. The 42nd Conference on Uncertainty in Artificial Intelligence (UAI). 2026. Soon
-
F. Baldo and C. K. Assaad. Regret-based federated causal discovery with unknown interventions. The 43rd International Conference on Machine Learning (ICML). 2026. Link
-
T. Loranchet and C. K. Assaad. Orientability of causal relations in time series using summary causal graphs and faithful distributions. Conference on Artificial Intelligence and Statistics (AISTATS). 2026.
Link
-
T. Loranchet and C. K. Assaad. Local Markov equivalence and local causal discovery for identifying controlled direct effects. The 5th Conference on Causal Learning and Reasoning (Clear). 2026.
Link (selected for an oral presentation)
-
F. Baldo, S. Ferreira and C. K. Assaad. Retrieving Classes of Causal Orders with Inconsistent Knowledge Bases. The 5th Conference on Causal Learning and Reasoning (Clear). 2026.
Link
-
S. Ferreira and C. K. Assaad. Identifying Macro Causal Effects in C-DMGs over DMGs. Advances in Neural Information Processing Systems (Neurips). 2025.
Link
-
-
S. Ferreira and C. K. Assaad. Identifying Macro Causal Effects in C-DMGs over ADMGs. Transactions on Machine Learning Research. 2025.
Link
-
C. K. Assaad. Towards identifiability of micro total effects in summary causal graphs with latent confounding: extension of the front-door criterion. Transactions on Machine Learning Research. 2025.
Link
-
C. K. Assaad. Causal reasoning in difference graphs. The 4th Conference on Causal Learning and Reasoning (CLeaR). 2025.
Link (selected for an oral presentation)
-
S. Ferreira and C. K. Assaad. Identifying macro conditional independencies and macro total effects in summary causal graphs with latent confounding. The 39th AAAI Conference on Artificial Intelligence. 2025.
Link (selected for an oral presentation)
-
B. Glemain, C. K. Assaad, W. Ghosn, P. Moulaire, X. de Lamballerie, M. Zins, G. Severi, M. Touvier, J.F. Deleuze, SAPRIS-SERO Study Group, N. Lapidus, F. Carrat. Revisiting the link between COVID-19 incidence and infection fatality rate during the first pandemic wave. 2025.
Link
-
L. Zan, C. K. Assaad, E. Devijver, E. Gaussier, and A. Ait-Bachir. On the fly detection of root causes from observed data with application to IT systems. ACM International
Conference on Information and Knowledge Management (CIKM). 2024.
Link
-
C. K. Assaad, E. Devijver, E. Gaussier, G. Goessler, and A. Meynaoui. Identifiability of total effects from abstractions of time series causal graphs. The 40th Conference on Uncertainty in Artificial Intelligence (UAI). 2024.
Link
-
D. Bystrova, C. K. Assaad, J. Arbel, E. Devijver, E. Gaussier, and W. Thuiller. Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms. Transactions on Machine Learning Research. 2024.
Link
-
A. Ruer, T. Loranchet, D. Bystrova and C. K. Assaad. Root cause analysis via difference graph discovery from linear time-series data. 2026.
Soon
-
W. Scott, E. Valdano and C. K. Assaad. Missing data and cluster graphs: cluster level missingness vs variable-level missingness. 2026.
Link
-
I. Belciug, S. Ferreira and C. K. Assaad. On efficient adjustment for micro causal effects in summary causal graphs. 2025.
Link
-
T. Loranchet, D. Bystrova, P. Burgat, J. Bellet, M. Bourlière, C. Lusivika-Nzinga, J. Nicol, L. Parlati, P-Y Boëlle, F. Carrat and C. K. Assaad. Local causal discovery in epidemiology: an application to quantifying the effect of diabetes on severe liver fibrosis in patients with viral hepatitis. 2025.
Link
-
C. Yvernes, C. K. Assaad, E. Devijver, and Eric Gaussier. Identifiability by common backdoor in summary causal graphs of time series. 2025.
Link
-
D. Bystrova, C. K. Assaad, S. Si-moussi, and W. Thuiller. Causal discovery from ecological time series with one timestamp and multiple observations. 2024.
Link
