Bradly C. Stadie

According to our database, Bradly C. Stadie authored at least 29 papers between 2015 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

TEMPO: Temporal Enforcement via Mode-Separated Policy Optimization for Trustworthy LLM Backtesting.

Zeyu Zhang, Bradly C. Stadie

CoRR, May, 2026

All Leaks Count, Some Count More: Interpretable Temporal Contamination Detection in LLM Backtesting.

Zeyu Zhang, Ryan Chen, Bradly C. Stadie

CoRR, February, 2026

Evolutionary System Prompt Learning for Reinforcement Learning in LLMs.

Lunjun Zhang, Ryan Chen, Bradly C. Stadie

CoRR, February, 2026

2025

AIA Forecaster: Technical Report.

Rohan Alur, Bradly C. Stadie, Daniel Kang, Ryan Chen, Matt McManus, Michael Rickert, Tyler Lee, Michael Federici, Richard Zhu, Dennis Fogerty, Hayley Williamson, Nina Lozinski, Aaron Linsky, Jasjeet S. Sekhon

CoRR, November, 2025

LAMP: Extracting Locally Linear Decision Surfaces from LLM World Models.

Ryan Chen, Youngmin Ko, Zeyu Zhang, Catherine Cho, Sunny Chung, Mauro Giuffrè, Dennis L. Shung, Bradly C. Stadie

CoRR, May, 2025

D2 Actor Critic: Diffusion Actor Meets Distributional Critic.

Lunjun Zhang, Shuo Han, Hanrui Lyu, Bradly C. Stadie

Trans. Mach. Learn. Res., 2025

Wonderful Team: Zero-Shot Physical Task Planning with Visual LLMs.

Zidan Wang, Rui Shen, Bradly C. Stadie

Trans. Mach. Learn. Res., 2025

Thoughts and Lessons on Using Visual Foundation Models for Manipulation.

Ryan Chen, Ziteng Pang, Bradly C. Stadie

Trans. Mach. Learn. Res., 2025

Expert of Experts Verification and Alignment (EVAL) Framework for Large Language Models Safety in Gastroenterology.

Mauro Giuffrè, Kisung You, Ziteng Pang, Simone Kresevic, Sunny Chung, Ryan Chen, Youngmin Ko, Colleen E. Chan, Theo Saarinen, Milos Ajcevic, Lory S. Crocè, Guadalupe Garcia-Tsao, Ian Gralnek, Joseph J. Y. Sung, Alan Barkun, Loren Laine, Jasjeet S. Sekhon, Bradly C. Stadie, Dennis L. Shung

npj Digit. Medicine, 2025

Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents.

Shuo Han, German Espinosa, Junda Huang, Daniel A. Dombeck, Malcolm A. MacIver, Bradly C. Stadie

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Solving Robotics Problems in Zero-Shot with Vision-Language Models.

Zidan Wang, Rui Shen, Bradly C. Stadie

CoRR, 2024

2023

To the Noise and Back: Diffusion for Shared Autonomy.

Takuma Yoneda, Luzhe Sun, Ge Yang, Bradly C. Stadie, Matthew R. Walter

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Cold Diffusion on the Replay Buffer: Learning to Plan from Known Good States.

Zidan Wang, Takeru Oba, Takuma Yoneda, Rui Shen, Matthew R. Walter, Bradly C. Stadie

Proceedings of the Conference on Robot Learning, 2023

2022

Understanding Hindsight Goal Relabeling Requires Rethinking Divergence Minimization.

Lunjun Zhang, Bradly C. Stadie

CoRR, 2022

Invariance Through Latent Alignment.

Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

2021

Invariance Through Inference.

Takuma Yoneda, Ge Yang, Matthew R. Walter, Bradly C. Stadie

CoRR, 2021

World Model as a Graph: Learning Latent Landmarks for Planning.

Lunjun Zhang, Ge Yang, Bradly C. Stadie

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Learning Intrinsic Rewards as a Bi-Level Optimization Problem.

Bradly C. Stadie, Lunjun Zhang, Jimmy Ba

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning.

Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba

Proceedings of the 37th International Conference on Machine Learning, 2020

One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation.

Matthew Shunshi Zhang, Bradly C. Stadie

Proceedings of the 8th International Conference on Learning Representations, 2020

2018

Learning as a Sampling Problem.

Bradly C. Stadie

PhD thesis, 2018

Transfer Learning for Estimating Causal Effects using Neural Networks.

Sören R. Künzel, Bradly C. Stadie, Nikita Vemuri, Varsha Ramakrishnan, Jasjeet S. Sekhon, Pieter Abbeel

CoRR, 2018

Some Considerations on Learning to Explore via Meta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

CoRR, 2018

Evolved Policy Gradients.

Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel

CoRR, 2018

The Importance of Sampling inMeta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Evolved Policy Gradients.

Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

One-Shot Imitation Learning.

Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Third Person Imitation Learning.

Bradly C. Stadie, Pieter Abbeel, Ilya Sutskever

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models.

Bradly C. Stadie, Sergey Levine, Pieter Abbeel

CoRR, 2015