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Active learning for data-efficient calibration of stochastic simulation models

Simulation-based calibration aims to infer unknown parameters of complex simulation models by aligning model outputs with real-world observations. When simulation runs are computationally expensive, statistical emulators trained on simulation data are used to efficiently approxim...