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Showing 1 to 3 of 3 for “"Bayes framework"”.
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Advances in Variational Bayes Theory: Adaptation, Uncertainty Quantification, and Amortization
… have been widely used in statistical physics, Bayesian posterior approximation, and modern generative modeling. At a high level, a variational method transforms an often difficult or intractable inference problem into an optimization problem by projecting a target distribution, under an …
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Natural Language Processing Reveals Patient Reported Experiences
… health crises, the lack of a guiding NLP framework to uncover patient-reported experiences for healthcare professionals, and absence of contextually-aware fine-grained emotion modeling in healthcare settings. Our research employs topic modeling, sentiment analysis, and probabilistic …
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Bayes Multiple Decision Functions: Theory, Computation and Application
… for each row the data may be low dimensional. A Bayesian decision-theoretic approach for this problem is implemented with the overall loss function being a cost-weighted linear combination of Type I and Type II loss functions. The class of loss functions considered allows for the use of the false …