9 citations · 10 across the 7 of their papers we have counts for
3 papers · 1 filter
A Langevin sampling algorithm inspired by the Adam optimizer
Benedict Leimkuhler, René Lohmann, Peter Whalley
We present a framework for adaptive-stepsize MCMC sampling based on time-rescaled Langevin dynamics, in which the stepsize variation is dynamically driven by an additional degree o…
Unbiased Kinetic Langevin Monte Carlo with Inexact Gradients
Neil K. Chada, Benedict Leimkuhler, Daniel Paulin +1
We present an unbiased method for Bayesian posterior means based on kinetic Langevin dynamics that combines advanced splitting methods with enhanced gradient approximations. Our ap…
Randomized Time Riemannian Manifold Hamiltonian Monte Carlo
Peter A. Whalley, Daniel Paulin, Benedict Leimkuhler
Hamiltonian Monte Carlo (HMC) algorithms which combine numerical approximation of Hamiltonian dynamics on finite intervals with stochastic refreshment and Metropolis correction are…