Post-hoc loss-calibration for Bayesian neural networks

Meet P. Vadera, Soumya Ghosh, Kenney Ng, Benjamin M. Marlin

Abstract: Bayesian decision theory provides an elegant framework for acting optimally under uncertainty when tractable posterior distributions are available. Modern Bayesian models, however, typically involv...