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05/06/2023
Trajectory-oriented optimization of stochastic epidemiological models
Epidemiological models must be calibrated to ground truth for downstream...
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04/27/2023
Developing Distributed High-performance Computing Capabilities of an Open Science Platform for Robust Epidemic Analysis
COVID-19 had an unprecedented impact on scientific collaboration. The pa...
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10/18/2021
A portfolio approach to massively parallel Bayesian optimization
One way to reduce the time of conducting optimization studies is to eval...
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01/15/2021
Sensitivity Prewarping for Local Surrogate Modeling
In the continual effort to improve product quality and decrease operatio...
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07/26/2019
Sequential Learning of Active Subspaces
In recent years, active subspace methods (ASMs) have become a popular me...
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02/18/2019
The Kalai-Smorodinski solution for many-objective Bayesian optimization
An ongoing aim of research in multiobjective Bayesian optimization is to...
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10/03/2018
On-site surrogates for large-scale calibration
Motivated by a challenging computer model calibration problem from the o...
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07/18/2018
Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation
We consider the problem of learning the level set for which a noisy blac...
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10/09/2017
Replication or exploration? Sequential design for stochastic simulation experiments
In this paper we investigate the merits of replication, and provide meth...
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04/18/2017
On the choice of the low-dimensional domain for global optimization via random embeddings
The challenge of taking many variables into account in optimization prob...
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11/08/2016
A Bayesian optimization approach to find Nash equilibria
Game theory finds nowadays a broad range of applications in engineering ...
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11/13/2014