2017
Date,Time,Room,Article,Discussant
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 Bootstrap, Matthias Reisser
Mar 13, 16:00-17:00, C3.211, Generalization and Equilibrium in Generative Adversarial Nets, Peter 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
2016
Date,Time,Room,Article,Discussant
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