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Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics
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theories from tractable models (probabilistic circuits) and Bayesian statistics to tackle the reliability of machine learning models, touching topics such as uncertainty quantification in large-scale models
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