302 citations · 518 across the 20 of their papers we have counts for
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Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov +3
Bayesian optimisation presents a sample-efficient methodology for global optimisation. Within this framework, a crucial performance-determining subroutine is the maximisation of th…
HEBO Pushing The Limits of Sample-Efficient Hyperparameter Optimisation
Alexander I. Cowen-Rivers, Wenlong Lyu, Rasul Tutunov +8
In this work we rigorously analyse assumptions inherent to black-box optimisation hyper-parameter tuning tasks. Our results on the Bayesmark benchmark indicate that heteroscedastic…
Generative Model-Enhanced Human Motion Prediction
Anthony Bourached, Ryan-Rhys Griffiths, Robert Gray +2
The task of predicting human motion is complicated by the natural heterogeneity and compositionality of actions, necessitating robustness to distributional shifts as far as out-of-…
Gaussian Process Molecule Property Prediction with FlowMO
Henry B. Moss, Ryan-Rhys Griffiths
We present FlowMO: an open-source Python library for molecular property prediction with Gaussian Processes. Built upon GPflow and RDKit, FlowMO enables the user to make predictions…
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes
Ryan-Rhys Griffiths, Jake L. Greenfield, Aditya R. Thawani +7
Photoswitchable molecules display two or more isomeric forms that may be accessed using light. Separating the electronic absorption bands of these isomers is key to selectively add…