Proposes a trajectory-oriented Bayesian optimization method using Gaussian process surrogates on parameters and seeds with adaptive Thompson sampling for efficient discovery of data-consistent trajectories in stochastic epidemic models.
The effects of common random numbers on stochastic kriging metamodels.ACM Transactions on Modeling and Computer Simulation (TOMACS), 22(2):1–20, 2012
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Staying on Track: Efficient Trajectory Discovery with Adaptive Batch Sampling
Proposes a trajectory-oriented Bayesian optimization method using Gaussian process surrogates on parameters and seeds with adaptive Thompson sampling for efficient discovery of data-consistent trajectories in stochastic epidemic models.