1 code implementation • 11 Sep 2019 • Tomasz Kuśmierczyk, Joseph Sakaya, Arto Klami
Bayesian models quantify uncertainty and facilitate optimal decision-making in downstream applications.
1 code implementation • NeurIPS 2019 • Tomasz Kuśmierczyk, Joseph Sakaya, Arto Klami
Bayesian decision theory outlines a rigorous framework for making optimal decisions based on maximizing expected utility over a model posterior.
no code implementations • 19 Apr 2017 • Joseph Sakaya, Arto Klami
Variational inference approximates the posterior distribution of a probabilistic model with a parameterized density by maximizing a lower bound for the model evidence.