447 citations · 3.6k across the 105 of their papers we have counts for
9 papers · 1 filter
Second Order Ensemble Langevin Method for Sampling and Inverse Problems
Ziming Liu, Andrew M. Stuart, Yixuan Wang
We propose a sampling method based on an ensemble approximation of second order Langevin dynamics. The log target density is appended with a quadratic term in an auxiliary momentum…
Consensus Based Sampling
J. A. Carrillo, F. Hoffmann, A. M. Stuart +1
We propose a novel method for sampling and optimization tasks based on a stochastic interacting particle system. We explain how this method can be used for the following two goals:…
Derivative-free Bayesian Inversion Using Multiscale Dynamics
G. A. Pavliotis, A. M. Stuart, U. Vaes
Inverse problems are ubiquitous because they formalize the integration of data with mathematical models. In many scientific applications the forward model is expensive to evaluate,…
Interacting Langevin Diffusions: Gradient Structure And Ensemble Kalman Sampler
Alfredo Garbuno-Inigo, Franca Hoffmann, Wuchen Li +1
Solving inverse problems without the use of derivatives or adjoints of the forward model is highly desirable in many applications arising in science and engineering. In this paper,…
Data Assimilation: A Mathematical Introduction
K. J. H. Law, A. M. Stuart, K. C. Zygalakis
These notes provide a systematic mathematical treatment of the subject of data assimilation.
Long-time Asymptotics of the Filtering Distribution for Partially Observed Chaotic Dynamical Systems
D. Sanz-Alonso, A. M. Stuart
The filtering distribution is a time-evolving probability distribution on the state of a dynamical system, given noisy observations. We study the large-time asymptotics of this pro…