The numerical methods are described in: Adrien Laurent, Gilles Vilmart, Order conditions for sampling the invariant measure of ergodic stochastic differential equations on manifolds, Found. Comput. Math. 22, 649–695 (2022) https://doi.org/10.1007/s10208-021-09495-y Content: - Julia implementation of the algorithm, - Output of the code for figures in the above research paper. - Matlab scripts for visualization. Version: August 10, 2021
International audienceIn this paper we propose a new approach for sampling from probability measures...
For sampling from a log-concave density, we study implicit integrators resulting from θ- method disc...
Abstract We introduce a novel geometry-informed irreversible perturbation that accele...
We derive a new methodology for the construction of high-order integrators for sampling the invarian...
We derive a new methodology for the construction of high order integrators for sampling the invarian...
We introduce new sufficient conditions for a numerical method to approximate with high order of accu...
We introduce new sufficient conditions for a numerical method to approximate with high order of accu...
International audienceWe introduce new sufficient conditions for a numerical method to approximate w...
We develop a framework that allows the use of the multi-level Monte Carlo (MLMC) methodology (Giles2...
The concept of effective order is a popular methodology in the deterministic literature for the cons...
International audienceThe concept of effective order is a popular methodology in the deterministic l...
International audienceWe consider numerical methods for thermodynamic sampling, i.e. computing seque...
We introduce a time-integrator to sample with high order of accuracy the invariant distribution for ...
In this paper we propose a new approach for sampling from probability measures in, possibly, high di...
We propose a computational method (with acronym ALDI) for sampling from a given target distribution ...
International audienceIn this paper we propose a new approach for sampling from probability measures...
For sampling from a log-concave density, we study implicit integrators resulting from θ- method disc...
Abstract We introduce a novel geometry-informed irreversible perturbation that accele...
We derive a new methodology for the construction of high-order integrators for sampling the invarian...
We derive a new methodology for the construction of high order integrators for sampling the invarian...
We introduce new sufficient conditions for a numerical method to approximate with high order of accu...
We introduce new sufficient conditions for a numerical method to approximate with high order of accu...
International audienceWe introduce new sufficient conditions for a numerical method to approximate w...
We develop a framework that allows the use of the multi-level Monte Carlo (MLMC) methodology (Giles2...
The concept of effective order is a popular methodology in the deterministic literature for the cons...
International audienceThe concept of effective order is a popular methodology in the deterministic l...
International audienceWe consider numerical methods for thermodynamic sampling, i.e. computing seque...
We introduce a time-integrator to sample with high order of accuracy the invariant distribution for ...
In this paper we propose a new approach for sampling from probability measures in, possibly, high di...
We propose a computational method (with acronym ALDI) for sampling from a given target distribution ...
International audienceIn this paper we propose a new approach for sampling from probability measures...
For sampling from a log-concave density, we study implicit integrators resulting from θ- method disc...
Abstract We introduce a novel geometry-informed irreversible perturbation that accele...