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cs.LG2021
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems
Meet P. Vadera, Benjamin M. Marlin
Approximate Bayesian deep learning methods hold significant promise for addressing several issues that occur when deploying deep learning components in intelligent systems, includi…
cs.LG2021★ 3 cited
Post-hoc loss-calibration for Bayesian neural networks
Meet P. Vadera, Soumya Ghosh, Kenney Ng +1
Bayesian decision theory provides an elegant framework for acting optimally under uncertainty when tractable posterior distributions are available. Modern Bayesian models, however,…