Tedrake, Russ

26 publications

ICML 2025 History-Guided Video Diffusion Kiwhan Song, Boyuan Chen, Max Simchowitz, Yilun Du, Russ Tedrake, Vincent Sitzmann

ICLR 2025 Should VLMs Be Pre-Trained with Image Data? Sedrick Keh, Jean Mercat, Samir Yitzhak Gadre, Kushal Arora, Igor Vasiljevic, Benjamin Burchfiel, Shuran Song, Russ Tedrake, Thomas Kollar, Ludwig Schmidt, Achal Dave

CoRL 2025 Steerable Scene Generation with Post Training and Inference-Time Search Nicholas Ezra Pfaff, Hongkai Dai, Sergey Zakharov, Shun Iwase, Russ Tedrake

NeurIPS 2024 Diffusion Forcing: Next-Token Prediction Meets Full-Sequence Diffusion Boyuan Chen, Diego Martí Monsó, Yilun Du, Max Simchowitz, Russ Tedrake, Vincent Sitzmann

ICML 2024 Lyapunov-Stable Neural Control for State and Output Feedback: A Novel Formulation Lujie Yang, Hongkai Dai, Zhouxing Shi, Cho-Jui Hsieh, Russ Tedrake, Huan Zhang

CoRL 2024 OpenVLA: An Open-Source Vision-Language-Action Model Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan P Foster, Pannag R Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn

ICLR 2024 Robot Fleet Learning via Policy Merging Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake

L4DC 2023 Can Direct Latent Model Learning Solve Linear Quadratic Gaussian Control? Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

ICLR 2023 Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision? Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

CoRL 2023 Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score Matching H.J. Terry Suh, Glen Chou, Hongkai Dai, Lujie Yang, Abhishek Gupta, Russ Tedrake

NeurIPS 2023 Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz, Russ Tedrake

NeurIPS 2023 Smoothed Online Learning for Prediction in Piecewise Affine Systems Adam Block, Max Simchowitz, Russ Tedrake

ICMLW 2023 Toward Understanding Latent Model Learning in MuZero: A Case Study in Linear Quadratic Gaussian Control Yi Tian, Kaiqing Zhang, Russ Tedrake, Suvrit Sra

ICML 2022 Do Differentiable Simulators Give Better Policy Gradients? Hyung Ju Suh, Max Simchowitz, Kaiqing Zhang, Russ Tedrake

NeurIPS 2022 Globally Convergent Policy Search for Output Estimation Jack Umenberger, Max Simchowitz, Juan Perdomo, Kaiqing Zhang, Russ Tedrake

CoRL 2022 Learning Multi-Object Dynamics with Compositional Neural Radiance Fields Danny Driess, Zhiao Huang, Yunzhu Li, Russ Tedrake, Marc Toussaint

CoRL 2021 Learning Models as Functionals of Signed-Distance Fields for Manipulation Planning Danny Driess, Jung-Su Ha, Marc Toussaint, Russ Tedrake

ICML 2020 FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis Aman Sinha, Matthew O’Kelly, Hongrui Zheng, Rahul Mangharam, John Duchi, Russ Tedrake

CoRL 2020 Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning Lucas Manuelli, Yunzhu Li, Pete Florence, Russ Tedrake

NeurIPS 2020 Neural Bridge Sampling for Evaluating Safety-Critical Autonomous Systems Aman Sinha, Matthew O'Kelly, Russ Tedrake, John C. Duchi

ICLR 2019 Evaluating Robustness of Neural Networks with Mixed Integer Programming Vincent Tjeng, Kai Y. Xiao, Russ Tedrake

ICLR 2019 Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluids Yunzhu Li, Jiajun Wu, Russ Tedrake, Joshua B. Tenenbaum, Antonio Torralba

CoRL 2018 Dense Object Nets: Learning Dense Visual Object Descriptors by and for Robotic Manipulation Peter R. Florence, Lucas Manuelli, Russ Tedrake

NeurIPS 2018 Scalable End-to-End Autonomous Vehicle Testing via Rare-Event Simulation Matthew O'Kelly, Aman Sinha, Hongseok Namkoong, Russ Tedrake, John C. Duchi

NeurIPS 2008 Signal-to-Noise Ratio Analysis of Policy Gradient Algorithms John W. Roberts, Russ Tedrake

AAAI 1999 Intelligent Agents in Computer Games Michael van Lent, John E. Laird, Josh Buckman, Joe Hartford, Steve Houchard, Kurt Steinkraus, Russ Tedrake