8 citations · 10 across the 5 of their papers we have counts for
7 papers
SABLE: Scalable Affine Bayesian Latent-space Exploration
Erik Bodin, Lisa Maria Kreusser, Donney Fan +3
Complex objects such as engineering designs and proteins are often difficult to optimise because their design spaces exhibit high-dimensional structure and objective evaluations ar…
Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization
Donney Fan, Colin Doumont, Aleksandra Kalisz +4
Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual screens to determine a set of c…
Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization
Donney Fan, Geoff Pleiss
In Bayesian optimization, Thompson sampling selects the evaluation point by sampling from the posterior distribution over the objective function maximizer. Because this sampling pr…
We Still Don't Understand High-Dimensional Bayesian Optimization
Colin Doumont, Donney Fan, Natalie Maus +3
Existing high-dimensional Bayesian optimization (BO) methods aim to overcome the curse of dimensionality by carefully encoding structural assumptions, from locality to sparsity to…
Asymmetric Duos: Sidekicks Improve Uncertainty
Tim G. Zhou, Evan Shelhamer, Geoff Pleiss
The go-to strategy to apply deep networks in settings where uncertainty informs decisions--ensembling multiple training runs with random initializations--is ill-suited for the extr…
MCMC-driven learning
Alexandre Bouchard-Côté, Trevor Campbell, Geoff Pleiss +1
This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chai…
Parametric Gaussian Process Regressors
Martin Jankowiak, Geoff Pleiss, Jacob R. Gardner
The combination of inducing point methods with stochastic variational inference has enabled approximate Gaussian Process (GP) inference on large datasets. Unfortunately, the result…