Gassiat, Élisabeth

8 publications

JMLR 2025 Frontiers to the Learning of Nonparametric Hidden Markov Models Kweku Abraham, Elisabeth Gassiat, Zacharie Naulet

JMLR 2025 Fundamental Limits of Membership Inference Attacks on Machine Learning Models Eric Aubinais, Elisabeth Gassiat, Pablo Piantanida

JMLR 2024 Additive Smoothing Error in Backward Variational Inference for General State-Space Models Mathis Chagneux, Elisabeth Gassiat, Pierre Gloaguen, Sylvain Le Corff

TMLR 2024 Variational Excess Risk Bound for General State Space Models Elisabeth Gassiat, Sylvain Le Corff

JMLR 2022 Multiple Testing in Nonparametric Hidden Markov Models: An Empirical Bayes Approach Kweku Abraham, Ismaël Castillo, Elisabeth Gassiat

NeurIPS 2021 Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä, Sylvain Le Corff, Luc Lehéricy, Jonathan So, Yongjie Zhu, Elisabeth Gassiat, Aapo Hyvarinen

JMLR 2020 Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy

JMLR 2016 Minimax Adaptive Estimation of Nonparametric Hidden Markov Models Yohann De Castro, Élisabeth Gassiat, Claire Lacour