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Title
Cited by
Cited by
Year
Proximal policy optimization algorithms
J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov
arXiv preprint arXiv:1707.06347, 2017
161672017
Improved techniques for training gans
T Salimans, I Goodfellow, W Zaremba, V Cheung, A Radford, X Chen
Advances in neural information processing systems 29, 2016
96392016
Language models are unsupervised multitask learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
OpenAI blog 1 (8), 9, 2019
88872019
Improving language understanding by generative pre-training
A Radford, K Narasimhan, T Salimans, I Sutskever
83292018
Openai gym
G Brockman, V Cheung, L Pettersson, J Schneider, J Schulman, J Tang, ...
arXiv preprint arXiv:1606.01540, 2016
69612016
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 29, 2016
51132016
Multi-agent actor-critic for mixed cooperative-competitive environments
R Lowe, YI Wu, A Tamar, J Harb, OAI Pieter Abbeel, I Mordatch
Advances in neural information processing systems 30, 2017
43622017
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
29852017
Glow: Generative flow with invertible 1x1 convolutions
DP Kingma, P Dhariwal
Advances in neural information processing systems 31, 2018
29692018
Hindsight experience replay
M Andrychowicz, F Wolski, A Ray, J Schneider, R Fong, P Welinder, ...
Advances in neural information processing systems 30, 2017
25822017
Concrete problems in AI safety
D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané
arXiv preprint arXiv:1606.06565, 2016
24332016
Weight normalization: A simple reparameterization to accelerate training of deep neural networks
T Salimans, DP Kingma
Advances in neural information processing systems 29, 2016
20862016
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 29, 2016
19482016
Deep reinforcement learning from human preferences
PF Christiano, J Leike, T Brown, M Martic, S Legg, D Amodei
Advances in neural information processing systems 30, 2017
18722017
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
16272017
Dota 2 with large scale deep reinforcement learning
C Berner, G Brockman, B Chan, V Cheung, P Dębiak, C Dennison, ...
arXiv preprint arXiv:1912.06680, 2019
16132019
Learning dexterous in-hand manipulation
OpenAI, M Andrychowicz, B Baker, M Chociej, R Józefowicz, B McGrew, ...
arXiv preprint arXiv:1808.00177, 2018
1551*2018
Generating long sequences with sparse transformers
R Child, S Gray, A Radford, I Sutskever
arXiv preprint arXiv:1904.10509, 2019
14602019
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
13712018
Adversarial training methods for semi-supervised text classification
T Miyato, AM Dai, I Goodfellow
arXiv preprint arXiv:1605.07725, 2016
11982016
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