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Hélène Halconruy

2 accepted papers

2025

Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups

ICML 2025poster

Markov processes serve as universal models for many real-world random processes. This paper presents a data-driven approach to learning these models through the spectral decomposition of the infinitesimal generator (IG) of the Markov semigroup. Its unbounded nature complicates traditional methods s…

Cited by 0SourcePDFScholar
2024

Learning the Infinitesimal Generator of Stochastic Diffusion Processes

NeurIPS 2024poster

We address data-driven learning of the infinitesimal generator of stochastic diffusion processes, essential for understanding numerical simulations of natural and physical systems. The unbounded nature of the generator poses significant challenges, rendering conventional analysis techniques for Hilb…

Cited by 4SourcePDFScholar