Zobrazeno 1 - 10
of 2 199
pro vyhledávání: '"Guillin, A."'
We present a method to obtain sharp local propagation of chaos results for a system of N particles with a diffusion coefficient that it not constant and may depend of the empirical measure. This extends the recent works of Lacker [14] and Wang [24] t
Externí odkaz:
http://arxiv.org/abs/2410.20874
Stochastic gradient descent with momentum is a popular variant of stochastic gradient descent, which has recently been reported to have a close relationship with the underdamped Langevin diffusion. In this paper, we establish a quantitative error est
Externí odkaz:
http://arxiv.org/abs/2410.17297
Autor:
Baderot, Julien, Cauchepin, Yann, Seiller, Alexandre, Fontanges, Richard, Martinez, Sergio, Foucher, Johann, Fuchs, Emmanuel, Daanoune, Mehdi, Grenier, Vincent, Barra, Vincent, Guillin, Arnaud
MicroLED displays are the result of a complex manufacturing chain. Each stage of this process, if optimized, contributes to achieving the highest levels of final efficiencies. Common works carried out by Pollen Metrology, Aledia, and Universit{\'e} C
Externí odkaz:
http://arxiv.org/abs/2410.21294
In this paper, we rigorously derive Central Limit Theorems (CLT) for Bayesian two-layerneural networks in the infinite-width limit and trained by variational inference on a regression task. The different networks are trained via different maximizatio
Externí odkaz:
http://arxiv.org/abs/2406.09048
In this paper, we prove in a very weak regularity setting existence and uniqueness of quasi-stationary distributions as well as exponential convergence towards the quasi-stationary distribution for the generalized Langevin and the Nos{\'e}-Hoover pro
Externí odkaz:
http://arxiv.org/abs/2403.17471
In this article, we focus on two toy models : the Curie-Weiss model and the system of $N$ particles in linear interactions in a double well confining potential. Both models, which have been extensively studied, describe a large system of particles wi
Externí odkaz:
http://arxiv.org/abs/2308.01624
We provide a rigorous analysis of training by variational inference (VI) of Bayesian neural networks in the two-layer and infinite-width case. We consider a regression problem with a regularized evidence lower bound (ELBO) which is decomposed into th
Externí odkaz:
http://arxiv.org/abs/2307.04779
Event-Chain Monte Carlo methods generate continuous-time and non-reversible Markov processes which often display important accelerations compared to their reversible counterparts. However their generalization to any system may appear less straightfor
Externí odkaz:
http://arxiv.org/abs/2307.02341
We consider a general system of two run-and-tumble particles interacting by hardcore jamming on the unidimensional torus. RTP are a paradigmatic active matter model, typically modeling the evolution of bacteria. By directly modeling the system at the
Externí odkaz:
http://arxiv.org/abs/2306.00831
Normalizing Flows (NF) are Generative models which are particularly robust and allow for exact sampling of the learned distribution. They however require the design of an invertible mapping, whose Jacobian determinant has to be computable. Recently i
Externí odkaz:
http://arxiv.org/abs/2302.01955