activity
20192021
most citedEmulation of physical processes with Emukit

56 citations · 118 across the 5 of their papers we have counts for

collaborators

10 papers

cs.LG202156 cited

Emulation of physical processes with Emukit

Andrei Paleyes, Mark Pullin, Maren Mahsereci +3

Decision making in uncertain scenarios is an ubiquitous challenge in real world systems. Tools to deal with this challenge include simulations to gather information and statistical…

cs.LG2021

GIBBON: General-purpose Information-Based Bayesian OptimisatioN

Henry B. Moss, David S. Leslie, Javier Gonzalez +1

This paper describes a general-purpose extension of max-value entropy search, a popular approach for Bayesian Optimisation (BO). A novel approximation is proposed for the informati…

cs.LG20212 cited

Good practices for Bayesian Optimization of high dimensional structured spaces

Eero Siivola, Javier Gonzalez, Andrei Paleyes +1

The increasing availability of structured but high dimensional data has opened new opportunities for optimization. One emerging and promising avenue is the exploration of unsupervi…

cs.LG202020 cited

BOSS: Bayesian Optimization over String Spaces

Henry B. Moss, Daniel Beck, Javier Gonzalez +2

This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops. R…

eess.AS2020

BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization

Henry B. Moss, Vatsal Aggarwal, Nishant Prateek +2

We present BOFFIN TTS (Bayesian Optimization For FIne-tuning Neural Text To Speech), a novel approach for few-shot speaker adaptation. Here, the task is to fine-tune a pre-trained…

cs.LG2019

BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design

Shali Jiang, Henry Chai, Javier Gonzalez +1

Finite-horizon sequential experimental design (SED) arises naturally in many contexts, including hyperparameter tuning in machine learning among more traditional settings. Computin…