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stat.ME2026
Independent Component Discovery in Temporal Count Data
Alexandre Chaussard, Anna Bonnet, Sylvain Le Corff
Advances in data collection are producing growing volumes of temporal count observations, making adapted modeling increasingly necessary. In this work, we introduce a generative fr…
stat.ME2024
Tree-based variational inference for Poisson log-normal models
Alexandre Chaussard, Anna Bonnet, Elisabeth Gassiat +1
When studying ecosystems, hierarchical trees are often used to organize entities based on proximity criteria, such as the taxonomy in microbiology, social classes in geography, or…
stat.ME2023
Variational excess risk bound for general state space models
Élisabeth Gassiat, Sylvain Le Corff
In this paper, we consider variational autoencoders (VAE) for general state space models. We consider a backward factorization of the variational distributions to analyze the exces…