Bayesian Deep Learning and Probabilistic Model Construction - ICML 2020 Tutorial

Bayesian Deep Learning and a Probabilistic Perspective of Model Construction ICML 2020 Tutorial Bayesian inference is especially compelling for deep neural networks. The key distinguishing property of a Bayesian approach is marginalization instead of optimization. Neural networks are typically underspecified by the data, and can represent many different but high performing models corresponding to different settings of parameters, which is exactly when marginalization will make the biggest difference for ac