3 papers
math.NA2025
Random Reshuffling for Stochastic Gradient Langevin Dynamics
Luke Shaw, Peter A. Whalley
We examine the use of different randomisation policies for stochastic gradient algorithms used in sampling, based on first-order (or overdamped) Langevin dynamics, the most popular…
stat.CO2025
Bayesian computation with generative diffusion models by Multilevel Monte Carlo
Abdul-Lateef Haji-Ali, Marcelo Pereyra, Luke Shaw +1
Generative diffusion models have recently emerged as a powerful strategy to perform stochastic sampling in Bayesian inverse problems, delivering remarkably accurate solutions for a…
math.OC2025
Randomised Splitting Methods and Stochastic Gradient Descent
Luke Shaw, Peter A. Whalley
We explore an explicit link between stochastic gradient descent using common batching strategies and splitting methods for ordinary differential equations. From this perspective, w…