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(November Series #4) Long-run Behaviour of Multi-fidelity Bayesian Optimisation

Join our November Research Series Talk #4 on November 28th at 2pm!

Nov. 24, 2023


(November Series #3) Closed-loop Optimisation of Deformable Mirrors for Laser Beam Aberration Correction

Join our November Research Series Talk #3 next Tuesday 5th Dec at 2pm!

Nov. 17, 2023


(November Series #2) Syngas Fermentation Optimisation with Mahdi Eskandari

Join our November Research Series Talk #2 next Tuesday at 2pm London!

Nov. 10, 2023

Screenshot 2023-11-10 at 10.07.37

(November Series #1) Search strategies for asynchronous parallel self-driving laboratories with pending points

Join our November Research Series Talk #1 next Wednesday at 2pm!

Nov. 1, 2023


HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO

The authors propose HPOBench, which includes 7 existing and 5 new benchmark families, with a total of more than 100 multi-fidelity benchmark problems.

Aug. 14, 2023


Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

The authors resolve the important open problem of deriving regret bounds for this setting, which imply novel convergence rates for GP optimization.

July 25, 2023


Multi-Fidelity Bayesian Optimization with Unreliable Information Sources

The authors propose rMFBO (robust MFBO), a methodology to make any GP-based MFBO scheme robust to the addition of unreliable information sources. rMFBO comes with a theoretical guarantee that its performance can be bound to its vanilla BO analog.

July 12, 2023

BNN architecture

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization

In this paper, the authors study BNNs as alternatives to standard GP surrogates for optimization. We consider a variety of approximate inference procedures for finite-width BNNs, including

July 7, 2023

uncertainty in bO graph

On the role of Model Uncertainties in Bayesian Optimization

In this work, the authors provide an extensive study of the relationship between the BO performance (regret) and uncertainty calibration for popular surrogate models and compare them across both synthetic and real-world experiments.

June 22, 2023


Causal Bayesian Optimization

This paper studies the problem of globally optimizing a variable of interest that is part of a causal model in which a sequence of interventions can be performed. This problem arises in biology, operational research, communications.

March 7, 2023

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