2021
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks
UAI 2021poster
Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that existing solutions dependent on simple Gaussian formulations may not be sufficient. However, moving to other distributions…