1 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
Vladimir R. Kostic, Karim Lounici, Hélène Halconruy +3
Markov processes serve as a universal model for many real-world random processes. This paper presents a data-driven approach for learning these models through the spectral decompos…
Learning the Infinitesimal Generator of Stochastic Diffusion Processes
Vladimir R. Kostic, Karim Lounici, Helene Halconruy +2
We address data-driven learning of the infinitesimal generator of stochastic diffusion processes, essential for understanding numerical simulations of natural and physical systems.…
Evolving privacy: drift parameter estimation for discretely observed i.i.d. diffusion processes under LDP
Chiara Amorino, Arnaud Gloter, Hélène Halconruy
The problem of estimating a parameter in the drift coefficient is addressed for discretely observed independent and identically distributed stochastic differential equations (S…