Bradly C. Stadie

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 24

Top Venues

CoRR

ICML

Robotics: Science and Systems

NeurIPS

University of California, Berkeley, USA (PHD)

Education History

University of California, Berkeley, USA

PHD

Publications

Zidan Wang, Rui Shen, Bradly C. Stadie
Solving Robotics Problems in Zero-Shot with Vision-Language Models. CoRR (2024)
Zidan Wang, Takeru Oba, Takuma Yoneda, Rui Shen, Matthew R. Walter, Bradly C. Stadie
Cold Diffusion on the Replay Buffer: Learning to Plan from Known Good States. CoRR (2023)
Takuma Yoneda, Luzhe Sun, Ge Yang, Bradly C. Stadie, Matthew R. Walter
To the Noise and Back: Diffusion for Shared Autonomy. Robotics: Science and Systems (2023)
Zidan Wang, Takeru Oba, Takuma Yoneda, Rui Shen, Matthew R. Walter, Bradly C. Stadie
Cold Diffusion on the Replay Buffer: Learning to Plan from Known Good States. CoRL (2023)
Takuma Yoneda, Luzhe Sun, Ge Yang, Bradly C. Stadie, Matthew R. Walter
To the Noise and Back: Diffusion for Shared Autonomy. CoRR (2023)
Lunjun Zhang, Bradly C. Stadie
Understanding Hindsight Goal Relabeling Requires Rethinking Divergence Minimization. CoRR (2022)
Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie
Invariance Through Latent Alignment. Robotics: Science and Systems (2022)
Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie
Invariance Through Inference. CoRR (2021)
Lunjun Zhang, Ge Yang, Bradly C. Stadie
World Model as a Graph: Learning Latent Landmarks for Planning. ICML (2021)
Matthew Shunshi Zhang, Bradly C. Stadie
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation. ICLR (2020)
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. ICML (2020)
Lunjun Zhang, Ge Yang, Bradly C. Stadie
World Model as a Graph: Learning Latent Landmarks for Planning. CoRR (2020)
Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. CoRR (2020)
Bradly C. Stadie, Lunjun Zhang, Jimmy Ba
Learning Intrinsic Rewards as a Bi-Level Optimization Problem. UAI (2020)
Matthew Shunshi Zhang, Bradly C. Stadie
One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation. CoRR (2019)
Sören R. Künzel, Bradly C. Stadie, Nikita Vemuri, Varsha Ramakrishnan, Jasjeet S. Sekhon, Pieter Abbeel
Transfer Learning for Estimating Causal Effects using Neural Networks. CoRR (2018)
Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel
Evolved Policy Gradients. CoRR (2018)
Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
Some Considerations on Learning to Explore via Meta-Reinforcement Learning. CoRR (2018)
Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
The Importance of Sampling inMeta-Reinforcement Learning. NeurIPS (2018)
Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel
Evolved Policy Gradients. NeurIPS (2018)
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba
One-Shot Imitation Learning. NIPS (2017)
Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever
Third Person Imitation Learning. ICLR (Poster) (2017)
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba
One-Shot Imitation Learning. CoRR (2017)
Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever
Third-Person Imitation Learning. CoRR (2017)
Bradly C. Stadie, Sergey Levine, Pieter Abbeel
Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models. CoRR (2015)

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Publication Activity (10 Years)

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Bradly C. Stadie