Course Material

• Exercise: PDF - Github Repo
• Slides: Will be upladed
• Suggested Readings:
  • Stochastic Backpropagation and Approximate Inference in Deep Generative Models, Rezende et al, ICML 2014
  • Weight Uncertainty in Neural networks, Blundell et. al.
  • Auto-Encoding Variational Bayes, Kingma & Welling
  • The Neural Autoregressive Distribution Estimator, Larochelle & Murray
  • Practical Variational Inference for Neural Networks, Graves et. al.