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Found 3 papers, 2 papers with code
Learning relevant contextual variables within Bayesian Optimization
Contextual Bayesian Optimization (CBO) efficiently optimizes black-box functions with respect to design variables, while simultaneously integrating contextual information regarding the environment, such as experimental conditions.
Projective Preferential Bayesian Optimization
This is demonstrated in a user experiment in which the user feedback comes in the form of optimal position and orientation of a molecule adsorbing to a surface.
DScribe: Library of Descriptors for Machine Learning in Materials Science
DScribe is a software package for machine learning that provides popular feature transformations ("descriptors") for atomistic materials simulations.
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