Approximate inference #5 - 15. Dec. 2016 - Christmas edition

Variational Tempering

http://jmlr.org/proceedings/papers/v51/mandt16.pdf

Approximate inference #4 - 24. Nov. 2016

Variational Message Passing 

http://www.jmlr.org/papers/volume6/winn05a/winn05a.pdf

Approximate inference #3 - 10. Nov. 2016

Stochastic Variational Inference

http://jmlr.org/papers/volume14/hoffman13a/hoffman13a.pdf

Approximate inference #2 - 27. Oct. 2016

An Introduction to Variational Methodsfor Graphical Models

https://people.eecs.berkeley.edu/~jordan/papers/variational-intro.pdf

Approximate inference #1 - 13. Oct. 2016

Graphical Models

https://www.cs.cmu.edu/~aarti/Class/10701/readings/graphical_model_Jordan.pdf

Deep Learning #10 - 29. Sep. 2016

Deep Learning #9 - 15. Sep. 2016

Learning to Communicate withDeep Multi-Agent Reinforcement Learning

https://arxiv.org/pdf/1605.06676v2.pdf

Deep Learning #8 - 23 June 2016 / 01. Sep. 2016

End-to-End Training of Deep Visuomotor Policies

https://arxiv.org/pdf/1504.00702v5.pdf

Deep Learning #7 - 9 June 2016

Benchmarking Deep Reinforcement Learning for Continuous Control

http://arxiv.org/pdf/1604.06778v2.pdf

Continuous control with deep reinforcement learning

http://arxiv.org/pdf/1509.02971v5.pdf

Deep Learning #6 - 26 May 2016

Playing atari with deep reinforcement learning 

http://arxiv.org/abs/1312.5602

Mastering the game of Go with deep neural networks and tree search

http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html

Deep Learning #5 - 12 May 2016

Variational Auto-encoded Deep Gaussian Processes
  http://arxiv.org/abs/1511.06455

Deep Learning #4 - 21 April 2016

Deep Learning #3 - 7 April 2016

ADVERSARIAL AUTOENCODERS- Goodfellow et.al (2016)

Deep Learning #2 - 24 March 2016

Represenation Learning: A Review and New Perspectives - Vincent et. al. (2014)

Deep Learning #1 - 10 March 2016

Deep Learning - Hinton et. al. (Nature, 2015)