Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension

2 August 2021

Papers citing "Asymptotic bias of inexact Markov Chain Monte Carlo methods in high dimension"

12 / 12 papers shown

Title
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks Emanuel Sommer Jakob Robnik Giorgi Nozadze U. Seljak David Rügamer BDL UQCV 84 1 0 10 Feb 2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics Luke Shaw Peter A. Whalley 93 3 0 28 Jan 2025
On theoretical guarantees and a blessing of dimensionality for nonconvex sampling Martin Chak 48 2 0 12 Nov 2024
Mixing of the No-U-Turn Sampler and the Geometry of Gaussian Concentration Nawaf Bou-Rabee Stefan Oberdörster 33 1 0 09 Oct 2024
Nonlinear Hamiltonian Monte Carlo & its Particle Approximation Nawaf Bou-Rabee Katharina Schuh 23 7 0 22 Aug 2023
Non-Log-Concave and Nonsmooth Sampling via Langevin Monte Carlo Algorithms Tim Tsz-Kit Lau Han Liu T. Pock 39 4 0 25 May 2023
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 32 12 0 20 Nov 2022
HMC and underdamped Langevin united in the unadjusted convex smooth case Nicolai Gouraud Pierre Le Bris Adrien Majka Pierre Monmarché 20 10 0 02 Feb 2022
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling Keru Wu S. Schmidler Yuansi Chen 39 50 0 27 Sep 2021
Mixing Time Guarantees for Unadjusted Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle 58 29 0 03 May 2021
Multi-index Antithetic Stochastic Gradient Algorithm Mateusz B. Majka Marc Sabate Vidales Łukasz Szpruch 34 0 0 10 Jun 2020
Coupling and Convergence for Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle Raphael Zimmer 77 136 0 01 May 2018