(Peter) Xi Chen
(Peter) Xi Chen | UC Berkeley
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Improved techniques for training gans
T Salimans, I Goodfellow, W Zaremba, V Cheung, A Radford, X Chen
Advances in Neural Information Processing Systems, 2226-2234, 2016
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel
Advances in Neural Information Processing Systems, 2172-2180, 2016
Improved variational inference with inverse autoregressive flow
DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling
Advances in Neural Information Processing Systems, 4743-4751, 2016
Benchmarking deep reinforcement learning for continuous control
Y Duan, X Chen, R Houthooft, J Schulman, P Abbeel
International Conference on Machine Learning, 1329-1338, 2016
Evolution strategies as a scalable alternative to reinforcement learning
T Salimans, J Ho, X Chen, S Sidor, I Sutskever
arXiv preprint arXiv:1703.03864, 2017
A Simple Neural Attentive Meta-Learner
N Mishra, M Rohaninejad, X Chen, P Abbeel
NIPS 2017 Workshop on Meta-Learning, 2017
RL : Fast Reinforcement Learning via Slow Reinforcement Learning
Y Duan, J Schulman, X Chen, PL Bartlett, I Sutskever, P Abbeel
arXiv preprint arXiv:1611.02779, 2016
Pixelcnn++: Improving the pixelcnn with discretized logistic mixture likelihood and other modifications
T Salimans, A Karpathy, X Chen, DP Kingma
arXiv preprint arXiv:1701.05517, 2017
VIME: Variational information maximizing exploration
R Houthooft, X Chen, Y Duan, J Schulman, F De Turck, P Abbeel
Advances in Neural Information Processing Systems, 1109-1117, 2016
Evaluating Protein Transfer Learning with TAPE
R Rao, N Bhattacharya, N Thomas, Y Duan, X Chen, J Canny, P Abbeel, ...
arXiv preprint arXiv:1906.08230, 2019
Variational Lossy Autoencoder
X Chen, DP Kingma, T Salimans, Y Duan, P Dhariwal, J Schulman, ...
International Conference on Learning Representations (ICLR), 2017
Parameter Space Noise for Exploration
M Plappert, R Houthooft, P Dhariwal, S Sidor, RY Chen, X Chen, T Asfour, ...
arXiv preprint arXiv:1706.01905, 2017
Deep imitation learning for complex manipulation tasks from virtual reality teleoperation
T Zhang, Z McCarthy, O Jowl, D Lee, X Chen, K Goldberg, P Abbeel
2018 IEEE International Conference on Robotics and Automation (ICRA), 1-8, 2018
# Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning
H Tang, R Houthooft, D Foote, A Stooke, X Chen, Y Duan, J Schulman, ...
arXiv preprint arXiv:1611.04717, 2016
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
D Ho, E Liang, I Stoica, P Abbeel, X Chen
arXiv preprint arXiv:1905.05393, 2019
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
J Ho, X Chen, A Srinivas, Y Duan, P Abbeel
arXiv preprint arXiv:1902.00275, 2019
Meta Learning Shared Hierarchies
K Frans, J Ho, X Chen, P Abbeel, J Schulman
arXiv preprint arXiv:1710.09767, 2017
Equivalence between policy gradients and soft q-learning
J Schulman, X Chen, P Abbeel
arXiv preprint arXiv:1704.06440, 2017
PixelSNAIL: An Improved Autoregressive Generative Model
X Chen, N Mishra, M Rohaninejad, P Abbeel
arXiv preprint arXiv:1712.09763, 2017
The Importance of Sampling inMeta-Reinforcement Learning
B Stadie, G Yang, R Houthooft, P Chen, Y Duan, Y Wu, P Abbeel, ...
Advances in Neural Information Processing Systems, 9299-9309, 2018
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