A mixed-variable Bayesian optimization framework based on latent variable Gaussian processes is developed and demonstrated on optimizing composition and morphology for insulating polymer nanocomposites, with an extension to multi-objective Pareto optimization.
Rapid Bayesian optimisation for synthesis of short polymer fiber materials,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.comp-ph 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Data-Centric Mixed-Variable Bayesian Optimization For Materials Design
A mixed-variable Bayesian optimization framework based on latent variable Gaussian processes is developed and demonstrated on optimizing composition and morphology for insulating polymer nanocomposites, with an extension to multi-objective Pareto optimization.