447 citations · 2.5k across the 63 of their papers we have counts for
65 papers
A randomized multi-index sequential Monte Carlo method
Xinzhu Liang, Shangda Yang, Simon L. Cotter +1
We consider the problem of estimating expectations with respect to a target distribution with an unknown normalizing constant, and where even the unnormalized target needs to be ap…
Mixtures of Gaussian Process Experts with SMC
Teemu Härkönen, Sara Wade, Kody Law +1
Gaussian processes are a key component of many flexible statistical and machine learning models. However, they exhibit cubic computational complexity and high memory constraints du…
Exponential Concentration in Stochastic Approximation
Kody Law, Neil Walton, Shangda Yang
We analyze the behavior of stochastic approximation algorithms where iterates, in expectation, progress towards an objective at each step. When progress is proportional to the step…
Digital Fingerprinting of Microstructures
Michael D. White, Alexander Tarakanov, Christopher P. Race +2
Finding efficient means of fingerprinting microstructural information is a critical step towards harnessing data-centric machine learning approaches. A statistical framework is sys…
Bayesian Deep Learning with Multilevel Trace-class Neural Networks
Neil K. Chada, Ajay Jasra, Kody J. H. Law +1
In this article we consider Bayesian inference associated to deep neural networks (DNNs) and in particular, trace-class neural network (TNN) priors which can be preferable to tradi…
Multi-index Sequential Monte Carlo ratio estimators for Bayesian Inverse problems
Kody J. H. Law, Neil Walton, Shangda Yang +1
We consider the problem of estimating expectations with respect to a target distribution with an unknown normalizing constant, and where even the unnormalized target needs to be ap…