Deep Learning

Research Frontiers in Bayesian Deep Learning and Posterior Inference

Investigation of probabilistic frameworks for quantifying parameter uncertainty in neural networks through variational inference, MCMC methods, and approximate posterior estimation techniques.

All Deep Learning PhD categories