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39 papers · 1 filter
Energy decomposition by potential level
Nicolas Bouleau
In the first part we study excessive functions for a Markov process that are continuous semimartingales along the sample paths. The property then follows from the theory of local t…
Asymptotic properties of the maximum likelihood estimator for Hidden Markov Models indexed by binary trees
Julien Weibel
We consider hidden Markov models indexed by a binary tree where the hidden state space is a general metric space. We study the maximum likelihood estimator (MLE) of the model param…
Constructive approaches to concentration inequalities with independent random variables
Celine Moucer, Adrien Taylor, Francis Bach
Concentration inequalities, a major tool in probability theory, quantify how much a random variable deviates from a certain quantity. This paper proposes a systematic convex optimi…
Mean-field limits for Consensus-Based Optimization and Sampling
Nicolai Jurek Gerber, Franca Hoffmann, Urbain Vaes
For algorithms based on interacting particle systems that admit a mean-field description, convergence analysis is often more accessible at the mean-field level. In order to transfe…
Conditioning Bienaym{é}-Galton-Watson trees to have large sub-populations
Romain Abraham, Hongwei Bi, Jean-François Delmas
We study the local limit in distribution of Bienaym{é}-Galton-Watson trees conditioned on having large sub-populations. Assuming a generic and aperiodic condition on the offspring…
Individual based SIS models on (not so) dense large random networks
Jean-François Delmas, Paolo Frasca, Federica Garin +3
Starting from a stochastic individual-based description of an SIS epidemic spreading on a random network, we study the dynamics when the size of the network tends to infinity.…