Complete Characterization for Adjustment in Summary Causal Graphs of Time Series
C. Yvernes, E. Devijver, E. Gaussier (2025). UAI

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning
S. Dong, M. Sebag, K. Uemura, A. Fujii, S. Chang, Y. Koyanagi, K. Maruhashi (2025) AAAI

Identifiability of total effects from abstractions of time series causal graphs,
C.K. Assaad, E. Devijver, E. Gaussier, G. Goessler, A. Meynaoui (2024). UAI

Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms,
D. Bystrova, C.K. Assaad, J. Arbel, E. Devijver, E. Gaussier, W. Thuillier (2024). TMLR

On the Fly Detection of Root Causes from Observed Data with Application to IT Systems,
L. Zan, A. Ait-Bachir, C. K. Assaad, E. Devijver, E. Gaussier (2024). CIKM

Difference graph over two populations: Implicit Difference Inference algorithm,
Daria Bystrova, Emilie Devijver, Vardan Manucharian, Julie Mondet, Pascal Mossuz (2024), 9th Causal Inference Workshop at UAI 2024