357 citations · 1.7k across the 74 of their papers we have counts for
8 papers · 1 filter
Some remarks on free energy and coarse-graining
Frederic Legoll, Tony Lelievre
We present recent results on coarse-graining techniques for thermodynamic quantities (canonical averages) and dynamical quantities (averages of path functionals over solutions of o…
Enhanced sampling of multidimensional free-energy landscapes using adaptive biasing forces
Chris Chipot, Tony Lelièvre
We propose an adaptive biasing algorithm aimed at enhancing the sampling of multimodal measures by Langevin dynamics. The underlying idea consists in generalizing the standard adap…
A multiple replica approach to simulate reactive trajectories
Frédéric Cérou, Arnaud Guyader, Tony Lelièvre +1
A method to generate reactive trajectories, namely equilibrium trajectories leaving a metastable state and ending in another one is proposed. The algorithm is based on simulating i…
Langevin dynamics with constraints and computation of free energy differences
Tony Lelievre, Mathias Rousset, Gabriel Stoltz
In this paper, we consider Langevin processes with mechanical constraints. The latter are a fundamental tool in molecular dynamics simulation for sampling purposes and for the comp…
A numerical closure approach for kinetic models of polymeric fluids: exploring closure relations for FENE dumbbells
Giovanni Samaey, Tony Lelievre, Vincent Legat
We propose a numerical procedure to study closure approximations for FENE dumbbells in terms of chosen macroscopic state variables, enabling to test straightforwardly which macrosc…
Reduced basis techniques for stochastic problems
Sébastien Boyaval, Claude Le Bris, Tony Lelièvre +3
We report here on the recent application of a now classical general reduction technique, the Reduced-Basis approach initiated in [C. Prud'homme, D. Rovas, K. Veroy, Y. Maday, A. T.…
Convergence of a greedy algorithm for high-dimensional convex nonlinear problems
Eric Cances, Virginie Ehrlacher, Tony Lelievre
In this article, we present a greedy algorithm based on a tensor product decomposition, whose aim is to compute the global minimum of a strongly convex energy functional. We prove…
Free Energy Methods for Bayesian Inference: Efficient Exploration of Univariate Gaussian Mixture Posteriors
Nicolas Chopin, Tony Lelievre, Gabriel Stoltz
Because of their multimodality, mixture posterior distributions are difficult to sample with standard Markov chain Monte Carlo (MCMC) methods. We propose a strategy to enhance the…