Seminario Datalab
Resolving the Incongruity between Variational Inference and MCMC with the Occlusion Process
Ponente: Max Hird (University of Waterloo)Fecha: jueves 07 de mayo de 2026 - 12:00Lugar: Aula Gris 3, ICMAT
Resumen:
Variational inference (VI) can be very fast, although it is inexact. Markov chain Monte Carlo (MCMC) is asymptotically exact but slow due to the fact that it is inherently serial. It is therefore an attractive prospect to combine the two to create an inference algorithm that is both fast and asymptotically exact. In doing so one encounters a fundamental tension between the two methods: VI produces an object (the variational approximation) that is fundamentally global whereas general purpose MCMC algorithms are fundamentally local. Naïvely combining the two may result in poor performance. We propose the Occlusion Process to resolve this incongruity and combine the best aspects of either method. Joint work with Florian Maire, available here: https://arxiv.org/abs/2411.11983.
