{'fraction_non_alphanumeric': 0.020151133501259445, 'fraction_numerical': 0.0, 'mean_word_length': 5.419354838709677, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Bayesian Experimental Design: A Review

This paper reviews the literature on Bayesian experimental design, both for linear and nonlinear models. A uniied view of the topic is presented by putting experimental design in a decision theoretic framework. This framework justiies many optimality criteria, and opens new possibilities. Various design criteria become part of a single, coherent approach.