Deep Bayes Reading Club



Aug 21,16:00-17:00, D1.160, Optimizing the latent space of Generative Adversarial Networks, Patrick Forré

Aug 14,16:00-17:00, D1.160, Adversarial Variational Bayes, Patrick Forré

Aug 07,16:00-17:00, C3.211, On Unifying Deep Generative Models, Bas Veeling

Jul 31, 16:00-17:00, C3.211, Variational Inference with Normalizing Flows , Karen Ullrich

Jul 17, 16:00-17:00, C3.211, Information Dropout, Matthias Reisser

Jul 10, 16:00-17:00, C3.211, Deep Variational information Bottleneck, Jakub Tomczak

Jun 12, 16:00-17:00, C3.211, VAE with a VampPrior, Jakub Tomczak

Apr 3, 16:00-17:00, C3.211, Learning structured weight uncertainty in Bayesian neural networks, Mijung Park

Mar 20, 16:00-17:00, C3.211, Approximate Bayesian inference with the weighted likelihood BootstrapMatthias Reisser

Mar 13, 16:00-17:00, C3.211, Generalization and Equilibrium in Generative Adversarial NetsPeter O’Connor

Mar 6, 16:00-17:00, C3.211, Improved generator objectives for GANs, Mijung Park

Feb 6, 16:00-17:00, C3.211, Wasserstein GAN, Mijung Park

Jan 30, 16:00-17:00, C3.211, Learning in implicit generative models, Christos Louizos

Jan 23, 16:00-17:00, C3.211, Hierarchical Variational Models, Christos Louizos

Jan 16, 16:00-17:00, C3.265, Boosting Variational Inference, Mijung Park



Nov 28, 16:00-17:00, C3.265, Optimizing Neural Networks with Kronecker-factored Approximate Curvature, Changyong Oh

Nov 21, 16:00-17:00, C3.265, Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm, Christos Louizos

Nov 14, 16:00-17:00, C3.265, Adversarial Autoencoders Jakub Tomczak

Nov 07, 16:00-17:00, C3.265, Why does deep and cheap learning work so well?, Thomas Kipf

Oct 17, 16:00-17:00, C3.265, A complete recipe for stochastic gradient MCMC, Mijung Park

Jul 11, 16:00-17:00, C3.265, A variational analysis of stochastic gradient algorithms, Mijung Park

Jun 06, 16:00-17:00, C3.265, Auxiliary deep generative models, Changyong Oh

May 30, 16:00-17:00, C3.265, Deconstructing the ladder network architecture, Thomas Kipf

May 12, 16:00-17:00, C3.211, Semi-supervised learning with ladder networks, Thomas Kipf

May 02, 16:00-17:00, C3.211, Deep Gaussian processes, Thomas Kipf

Apr 25, 16:00-17:00, C3.211, The variational fair auto encoder and Variational autoencoded deep Gaussian processes , Christos Louizos