12.**Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks** ICLR 2017. [paper](https://arxiv.org/abs/1605.07127)
*Stefan Depeweg, José Miguel Hernández-Lobato, Finale Doshi-Velez, Steffen Udluft*
### Distributed Training
1.**Asynchronous Methods for Deep Reinforcement Learning** ICML 2016. [paper](https://arxiv.org/pdf/1602.01783.pdf)
*Volodymyr Mnih, Adrià Puigdomènech Badia, Mehdi Mirza, Alex Graves, Timothy P. Lillicrap, Tim Harley, David Silver, Koray Kavukcuoglu*
2.**GA3C: GPU-based A3C for Deep Reinforcement Learning** NIPS 2016. [paper](https://www.researchgate.net/publication/310610848_GA3C_GPU-based_A3C_for_Deep_Reinforcement_Learning)
*Iuri Frosio, Stephen Tyree Jason Clemons Jan Kautz*
*Gabriel Barth-Maron, Matthew W. Hoffman, David Budden, Will Dabney, Dan Horgan, Dhruva TB, Alistair Muldal, Nicolas Heess, Timothy Lillicrap*
6.**Emergence of Locomotion Behaviours in Rich Environments** arXiv. [paper](https://arxiv.org/abs/1707.02286)
*Nicolas Heess, Dhruva TB, Srinivasan Sriram, Jay Lemmon, Josh Merel, Greg Wayne, Yuval Tassa, Tom Erez, Ziyu Wang, S. M. Ali Eslami, Martin Riedmiller, David Silver*
7.**Recurrent Experience Replay in Distributed Reinforcement Learning** ICLR 2019. [paper](https://openreview.net/pdf?id=r1lyTjAqYX)
*Steven Kapturowski, Georg Ostrovski, John Quan, Remi Munos, Will Dabney*
8.**GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning** CoRL 2018. [paper](https://arxiv.org/abs/1810.05762)
*Jacky Liang, Viktor Makoviychuk, Ankur Handa, Nuttapong Chentanez, Miles Macklin, Dieter Fox*