A summary and comparision of three papers that handle uncertainty estimation with deep networks. This essay discusses "Bayes by Backprop", "Deep Ensembles" and "SWA-Gaussian".
A summary and comparision of three papers that handle data with missing or noisy labels. This essay discusses FixMatch, DivideMix, and SimCLR.
A summary and comparision of three papers that handle Deep Generative Models. This essay discusses StyleGAN2, hierarchical variational auto encoders, and Generative Flows.