357 citations · 1.7k across the 74 of their papers we have counts for
28 papers · 1 filter
Reduced basis method for non-symmetric eigenvalue problems: application to the multigroup neutron diffusion equations
Yonah Conjungo Taumhas, Geneviève Dusson, Virginie Ehrlacher +2
In this article, we propose a reduced basis method for parametrized non-symmetric eigenvalue problems arising in the loading pattern optimization of a nuclear core in neutronics. T…
Unbiasing Hamiltonian Monte Carlo algorithms for a general Hamiltonian function
Tony Lelièvre, Régis Santet, Gabriel Stoltz
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo method that allows to sample high dimensional probability measures. It relies on the integration of the Hamiltonian dyna…
Combining machine-learned and empirical force fields with the parareal algorithm: application to the diffusion of atomistic defects
Olga Gorynina, Frederic Legoll, Tony Lelievre +1
We numerically investigate an adaptive version of the parareal algorithm in the context of molecular dynamics. This adaptive variant has been originally introduced in [F. Legoll, T…
Using Witten Laplacians to locate index-1 saddle points
Tony Lelièvre, Panos Parpas
We introduce a new stochastic algorithm to locate the index-1 saddle points of a function , with possibly large. This algorithm can be seen as an e…
Influence of sampling on the convergence rates of greedy algorithms for parameter-dependent random variables
Mohamed-Raed Blel, Virginie Ehrlacher, Tony Lelièvre
The main focus of this article is to provide a mathematical study of the algorithm proposed in \cite{boyaval2010variance} where the authors proposed a variance reduction technique…
Multiple projection MCMC algorithms on submanifolds
Tony Lelièvre, Gabriel Stoltz, Wei Zhang
We propose new Markov Chain Monte Carlo algorithms to sample probability distributions on submanifolds, which generalize previous methods by allowing the use of set-valued maps in…