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Found 4 papers, 1 papers with code
GPflowOpt: A Bayesian Optimization Library using TensorFlow
A novel Python framework for Bayesian optimization known as GPflowOpt is introduced.
Hypervolume-based Multi-objective Bayesian Optimization with Student-t Processes
Student-$t$ processes have recently been proposed as an appealing alternative non-parameteric function prior.
Active Learning for Approximation of Expensive Functions with Normal Distributed Output Uncertainty
When approximating a black-box function, sampling with active learning focussing on regions with non-linear responses tends to improve accuracy.
Fast Calculation of the Knowledge Gradient for Optimization of Deterministic Engineering Simulations
A novel efficient method for computing the Knowledge-Gradient policy for Continuous Parameters (KGCP) for deterministic optimization is derived.
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