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.
Augmenting a simulation campaign for hybrid computer model and field data experiments.Technometrics, 66(4):638–650
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.