Devijver, Emilie

13 publications

UAI 2025 Complete Characterization for Adjustment in Summary Causal Graphs of Time Series Clément Yvernes, Emilie Devijver, Eric Gaussier

NeurIPS 2025 Relaxing Partition Admissibility in Cluster-DAGs: A Causal Calculus with Arbitrary Variable Clustering Clément Yvernes, Emilie Devijver, Adèle H. Ribeiro, Marianne Clausel, Eric Gaussier

TMLR 2024 Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms Daria Bystrova, Charles K. Assaad, Julyan Arbel, Emilie Devijver, Eric Gaussier, Wilfried Thuiller

UAI 2024 Identifiability of Total Effects from Abstractions of Time Series Causal Graphs Charles K. Assaad, Emilie Devijver, Eric Gaussier, Gregor Goessler, Anouar Meynaoui

JMLR 2024 Multi-Class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

IJCAI 2023 Survey and Evaluation of Causal Discovery Methods for Time Series (Extended Abstract) Charles K. Assaad, Emilie Devijver, Éric Gaussier

NeurIPSW 2023 Tree-Based Quantile Active Learning for Automated Discovery of MOFs Ashna Jose, Emilie Devijver, Noel Jakse, Valérie Monbet, Roberta Poloni

UAI 2022 Discovery of Extended Summary Graphs in Time Series Charles K. Assaad, Emilie Devijver, Eric Gaussier

JAIR 2022 Survey and Evaluation of Causal Discovery Methods for Time Series Charles K. Assaad, Emilie Devijver, Éric Gaussier

ECML-PKDD 2021 A Mixed Noise and Constraint-Based Approach to Causal Inference in Time Series Charles K. Assaad, Emilie Devijver, Éric Gaussier, Ali Aït-Bachir

JMLR 2020 Prediction Regions Through Inverse Regression Emilie Devijver, Emeline Perthame

NeurIPS 2020 Smooth and Consistent Probabilistic Regression Trees Sami Alkhoury, Emilie Devijver, Marianne Clausel, Myriam Tami, Eric Gaussier, Georges Oppenheim

AAAI 2019 Transductive Bounds for the Multi-Class Majority Vote Classifier Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini