most citedMultifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes

14 citations · 14 across the 1 of their papers we have counts for

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stat.CO2021★ 14 cited

Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes

David J. Warne, Thomas P. Prescott, Ruth E. Baker +1

Models of stochastic processes are widely used in almost all fields of science. Theory validation, parameter estimation, and prediction all require model calibration and statistica…