Statistical methods are leveraged in many scientific applications to: specify a data collection practice (experimental design), draw conclusions from sparse and noisy data (inference), and assess uncertainty about those conclusions (uncertainty quantification). Bayesian inference and experimental design methods are increasingly used in scientific practice, and offer appealing theoretical guarantees when certain assumptions hold. However, whether these assumptions hold is difficult or impossible…
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