103 citations · 325 across the 14 of their papers we have counts for
3 papers · 1 filter
Transport meets Variational Inference: Controlled Monte Carlo Diffusions
Francisco Vargas, Shreyas Padhy, Denis Blessing +1
Connecting optimal transport and variational inference, we present a principled and systematic framework for sampling and generative modelling centred around divergences on path sp…
Kernel Regression with Infinite-Width Neural Networks on Millions of Examples
Ben Adlam, Jaehoon Lee, Shreyas Padhy +2
Neural kernels have drastically increased performance on diverse and nonstandard data modalities but require significantly more compute, which previously limited their application…
Sampling-based inference for large linear models, with application to linearised Laplace
Javier Antorán, Shreyas Padhy, Riccardo Barbano +3
Large-scale linear models are ubiquitous throughout machine learning, with contemporary application as surrogate models for neural network uncertainty quantification; that is, the…