Bradly Stadie
Bradly Stadie
Research Assistant Professor, TTIC
Verified email at - Homepage
Cited by
Cited by
One-shot imitation learning
Y Duan, M Andrychowicz, BC Stadie, J Ho, J Schneider, I Sutskever, ...
arXiv preprint arXiv:1703.07326, 2017
Incentivizing exploration in reinforcement learning with deep predictive models
BC Stadie, S Levine, P Abbeel
arXiv preprint arXiv:1507.00814, 2015
Third-person imitation learning
BC Stadie, P Abbeel, I Sutskever
arXiv preprint arXiv:1703.01703, 2017
Evolved policy gradients
R Houthooft, RY Chen, P Isola, BC Stadie, F Wolski, J Ho, P Abbeel
arXiv preprint arXiv:1802.04821, 2018
Some considerations on learning to explore via meta-reinforcement learning
BC Stadie, G Yang, R Houthooft, X Chen, Y Duan, Y Wu, P Abbeel, ...
arXiv preprint arXiv:1803.01118, 2018
Maximum entropy gain exploration for long horizon multi-goal reinforcement learning
S Pitis, H Chan, S Zhao, B Stadie, J Ba
International Conference on Machine Learning, 7750-7761, 2020
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 31, 9280-9290, 2018
Transfer learning for estimating causal effects using neural networks
SR Künzel, BC Stadie, N Vemuri, V Ramakrishnan, JS Sekhon, P Abbeel
arXiv preprint arXiv:1808.07804, 2018
One-shot pruning of recurrent neural networks by jacobian spectrum evaluation
MS Zhang, B Stadie
arXiv preprint arXiv:1912.00120, 2019
World model as a graph: Learning latent landmarks for planning
L Zhang, G Yang, BC Stadie
International Conference on Machine Learning, 12611-12620, 2021
Learning intrinsic rewards as a bi-level optimization problem
B Stadie, L Zhang, J Ba
Conference on Uncertainty in Artificial Intelligence, 111-120, 2020
Simulating the stochastic dynamics and cascade failure of power networks
C Matthews, B Stadie, J Weare, M Anitescu, C Demarco
arXiv preprint arXiv:1806.02420, 2018
Estimating heterogeneous treatment effects using neural networks with the Y-Learner
BC Stadie, SR Künzel, N Vemuri, JS Sekhon
One Demonstration Imitation Learning
BC Stadie, S Zhao, Q Xu, B Li, L Zhang
Learning as a Sampling Problem
BC Stadie
UC Berkeley, 2018
World Model as a Graph: Learning Latent Landmarks for Planning Supplementary Materials
L Zhang, G Yang, B Stadie
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning Download PDF
S Pitis, H Chan, S Zhao, B Stadie, J Ba
Evolved Policy Gradients: Supplementary Materials
R Houthooft, RY Chen, P Isola, BC Stadie, F Wolski, J Ho, P Abbeel
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