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20222026
most citedContraction and Convergence Rates for Discretized Kinetic Langevin Dynamics

9 citations · 10 across the 7 of their papers we have counts for

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math.PR2026

Theoretical guarantees for stochastic gradient Langevin dynamics

Daniel Paulin, Peter A. Whalley

We prove asymptotic bias bounds for stochastic gradient Langevin dynamics in Wasserstein distance of order two. We assume that the negative log-density is strongly convex with a Li…

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…