OpenAI
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OpenAI
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Title
Cited by
Cited by
Year
Improved techniques for training gans
T Salimans, I Goodfellow, W Zaremba, V Cheung, A Radford, X Chen
arXiv preprint arXiv:1606.03498, 2016
50042016
Proximal policy optimization algorithms
J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov
arXiv preprint arXiv:1707.06347, 2017
41722017
Infogan: Interpretable representation learning by information maximizing generative adversarial nets
X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel
arXiv preprint arXiv:1606.03657, 2016
27442016
Openai gym
G Brockman, V Cheung, L Pettersson, J Schneider, J Schulman, J Tang, ...
arXiv preprint arXiv:1606.01540, 2016
25212016
Improving language understanding by generative pre-training
A Radford, K Narasimhan, T Salimans, I Sutskever
19492018
Language models are unsupervised multitask learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
OpenAI blog 1 (8), 9, 2019
13512019
Multi-agent actor-critic for mixed cooperative-competitive environments
R Lowe, Y Wu, A Tamar, J Harb, P Abbeel, I Mordatch
arXiv preprint arXiv:1706.02275, 2017
12352017
Weight normalization: A simple reparameterization to accelerate training of deep neural networks
T Salimans, DP Kingma
arXiv preprint arXiv:1602.07868, 2016
11272016
Domain randomization for transferring deep neural networks from simulation to the real world
J Tobin, R Fong, A Ray, J Schneider, W Zaremba, P Abbeel
2017 IEEE/RSJ international conference on intelligent robots and systems …, 2017
11182017
Concrete problems in AI safety
D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané
arXiv preprint arXiv:1606.06565, 2016
10312016
Improving variational inference with inverse autoregressive flow
DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling
arXiv preprint arXiv:1606.04934, 2016
10082016
Glow: Generative flow with invertible 1x1 convolutions
DP Kingma, P Dhariwal
arXiv preprint arXiv:1807.03039, 2018
9622018
Hindsight experience replay
M Andrychowicz, F Wolski, A Ray, J Schneider, R Fong, P Welinder, ...
arXiv preprint arXiv:1707.01495, 2017
9362017
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
8182017
Openai baselines
P Dhariwal, C Hesse, O Klimov, A Nichol, M Plappert, A Radford, ...
6742017
Learning dexterous in-hand manipulation
OpenAI, M Andrychowicz, B Baker, M Chociej, R Józefowicz, B McGrew, ...
arXiv preprint arXiv:1808.00177, 2018
558*2018
Sim-to-real transfer of robotic control with dynamics randomization
XB Peng, M Andrychowicz, W Zaremba, P Abbeel
2018 IEEE international conference on robotics and automation (ICRA), 3803-3810, 2018
5012018
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
4852017
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
4802016
Vime: Variational information maximizing exploration
R Houthooft, X Chen, Y Duan, J Schulman, F De Turck, P Abbeel
arXiv preprint arXiv:1605.09674, 2016
4572016
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