1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2026
Generative Models as Adaptive Trust Regions for Discrete Bayesian Optimisation
Michael Dodds, Erik Bodin, Sebastian W. Ober +3
Bayesian optimisation (BO) is a powerful framework for sample-efficient optimisation of expensive black-box functions, but its application to high-dimensional discrete scientific d…
cs.DC2024★ 1 cited
Navigating the Maize: Cyclic and conditional computational graphs for molecular simulation
Thomas Löhr, Michele Assante, Michael Dodds +5
Many computational chemistry and molecular simulation workflows can be expressed as graphs. This abstraction is useful to modularize and potentially reuse existing components, as w…