activity
20192021
most citedStein Variational Gradient Descent: many-particle and long-time asymptotics

4 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

math.AP2021

Gradient flows for bounded linear evolution equations

D. R. Michiel Renger, Stefanie Schindler

We study linear evolution equations in separable Hilbert spaces defined by a bounded linear operator. We answer the question which of these equations can be written as a gradient f…

stat.ML20214 cited

Stein Variational Gradient Descent: many-particle and long-time asymptotics

Nikolas Nüsken, D. R. Michiel Renger

Stein variational gradient descent (SVGD) refers to a class of methods for Bayesian inference based on interacting particle systems. In this paper, we consider the originally propo…

math.CA2020

Fast reaction limits via -convergence of the Flux Rate Functional

Mark A. Peletier, D. R. Michiel Renger

We study the convergence of a sequence of evolution equations for measures supported on the nodes of a graph. The evolution equations themselves can be interpreted as the forward K…

cond-mat.stat-mech2020

Dynamical Phase Transitions for Flows on Finite Graphs

Davide Gabrielli, D. R. Michiel Renger

We study the time-averaged flow in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but…

math-ph2019

Orthogonality of Fluxes in General Nonlinear Reaction Networks

Johannes Zimmer, D. R. Michiel Renger

We consider the chemical reaction networks and study currents in these systems. Reviewing recent decomposition of rate functionals from large deviation theory for Markov processes,…