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02/16/2023
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow
We present Trieste, an open-source Python package for Bayesian optimizat...
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04/11/2022
{PF}^2ES: Parallel Feasible Pareto Frontier Entropy Search for Multi-Objective Bayesian Optimization Under Unknown Constraints
We present Parallel Feasible Pareto Frontier Entropy Search ({PF}^2ES) –...
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01/26/2021
Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems
Given their substantial success in addressing a wide range of computer v...
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11/10/2017
GPflowOpt: A Bayesian Optimization Library using TensorFlow
A novel Python framework for Bayesian optimization known as GPflowOpt is...
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02/02/2017
Sensitivity Analysis of Expensive Black-Box Systems Using Metamodeling
Simulations are becoming ever more common as a tool for designing comple...
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08/18/2016
Active Learning for Approximation of Expensive Functions with Normal Distributed Output Uncertainty
When approximating a black-box function, sampling with active learning f...
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08/16/2016