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stat.ML2024
Sampling from Bayesian Neural Network Posteriors with Symmetric Minibatch Splitting Langevin Dynamics
Daniel Paulin, Peter A. Whalley, Neil K. Chada +1
We propose a scalable kinetic Langevin dynamics algorithm for sampling parameter spaces of big data and AI applications. Our scheme combines a symmetric forward/backward sweep over…
math.PR2024★ 1 cited
Convergence of kinetic Langevin samplers for non-convex potentials
Katharina Schuh, Peter A. Whalley
We study three kinetic Langevin samplers including the Euler discretization, the BU and the UBU splitting scheme. We provide contraction results in -Wasserstein distance for n…
stat.ML2024
Correction to "Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations"
Daniel Paulin, Peter A. Whalley
A method for analyzing non-asymptotic guarantees of numerical discretizations of ergodic SDEs in Wasserstein-2 distance is presented by Sanz-Serna and Zygalakis in ``Wasserstein di…