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Zhoubo01 papers (#132)

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12. **Learning and Policy Search in Stochastic Dynamical Systems with Bayesian Neural Networks** ICLR 2017. [paper](https://arxiv.org/abs/1605.07127) 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* *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*
3. **Distributed Prioritized Experience Replay** ICLR 2018. [paper](https://openreview.net/pdf?id=H1Dy---0Z)
*Dan Horgan, John Quan, David Budden, Gabriel Barth-Maron, Matteo Hessel, Hado van Hasselt, David Silver*
4. **IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures** ICML 2018. [paper](https://arxiv.org/abs/1802.01561)
*Lasse Espeholt, Hubert Soyer, Remi Munos, Karen Simonyan, Volodymir Mnih, Tom Ward, Yotam Doron, Vlad Firoiu, Tim Harley, Iain Dunning, Shane Legg, Koray Kavukcuoglu*
5. **Distributed Distributional Deterministic Policy Gradients** ICLR 2018. [paper](https://arxiv.org/pdf/1804.08617.pdf)
*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*
9. **SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark** CoRL 2018. [paper](https://surreal.stanford.edu/img/surreal-corl2018.pdf)
*Linxi Fan, Yuke Zhu, Jiren Zhu, Zihua Liu, Orien Zeng, Anchit Gupta, Joan Creus-Costa, Silvio Savarese, Li Fei-Fei*
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