Majumdar, Anirudha

24 publications

ICLR 2025 Diffusion Policy Policy Optimization Allen Z. Ren, Justin Lidard, Lars Lien Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, Max Simchowitz

CoRL 2025 Generating Robot Constitutions & Benchmarks for Semantic Safety Pierre Sermanet, Anirudha Majumdar, Alex Irpan, Dmitry Kalashnikov, Vikas Sindhwani

CoRL 2025 Predictive Red Teaming: Breaking Policies Without Breaking Robots Anirudha Majumdar, Mohit Sharma, Dmitry Kalashnikov, Sumeet Singh, Pierre Sermanet, Vikas Sindhwani

CoRL 2025 SIREN: Semantic, Initialization-Free Registration of Multi-Robot Gaussian Splatting Maps Olao Shorinwa, Jiankai Sun, Mac Schwager, Anirudha Majumdar

CoRL 2025 WoMAP: World Models for Embodied Open-Vocabulary Object Localization Tenny Yin, Zhiting Mei, Tao Sun, Ola Sho, Anirudha Majumdar, Emily Zhou, Jeremy Bao, Miyu Yamane, Lihan Zha

CoRL 2024 Perceive with Confidence: Statistical Safety Assurances for Navigation with Learning-Based Perception Anushri Dixit, Zhiting Mei, Meghan Booker, Mariko Storey-Matsutani, Allen Z. Ren, Anirudha Majumdar

AAAI 2024 Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees (Abstract Reprint) Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime F. Fisac

CoRL 2023 AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer Allen Z. Ren, Hongkai Dai, Benjamin Burchfiel, Anirudha Majumdar

ICML 2023 Fundamental Tradeoffs in Learning with Prior Information Anirudha Majumdar

CoRL 2023 Online Learning for Obstacle Avoidance David Snyder, Meghan Booker, Nathaniel Simon, Wenhan Xia, Daniel Suo, Elad Hazan, Anirudha Majumdar

NeurIPS 2023 PAC-Bayes Generalization Certificates for Learned Inductive Conformal Prediction Apoorva Sharma, Sushant Veer, Asher Hancock, Heng Yang, Marco Pavone, Anirudha Majumdar

CoRL 2023 Robots That Ask for Help: Uncertainty Alignment for Large Language Model Planners Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar

CoRL 2022 Leveraging Language for Accelerated Learning of Tool Manipulation Allen Z. Ren, Bharat Govil, Tsung-Yen Yang, Karthik R Narasimhan, Anirudha Majumdar

ICLRW 2022 Sim-to-Lab-to-Real: Safe RL with Shielding and Generalization Guarantees Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime Fernández Fisac

NeurIPSW 2022 Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees Kai-Chieh Hsu, Allen Z. Ren, Duy Phuong Nguyen, Anirudha Majumdar, Jaime Fernández Fisac

ICML 2021 A Regret Minimization Approach to Iterative Learning Control Naman Agarwal, Elad Hazan, Anirudha Majumdar, Karan Singh

NeurIPS 2021 Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability Alec Farid, Anirudha Majumdar

L4DC 2021 Generating Adversarial Disturbances for Controller Verification Udaya Ghai, David Snyder, Anirudha Majumdar, Elad Hazan

L4DC 2021 Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning Anoopkumar Sonar, Vincent Pacelli, Anirudha Majumdar

L4DC 2021 Learning to Actively Reduce Memory Requirements for Robot Control Tasks Meghan Booker, Anirudha Majumdar

CoRL 2021 Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning Alec Farid, Sushant Veer, Anirudha Majumdar

CoRL 2020 Generalization Guarantees for Imitation Learning Allen Ren, Sushant Veer, Anirudha Majumdar

CoRL 2020 Probably Approximately Correct Vision-Based Planning Using Motion Primitives Sushant Veer, Anirudha Majumdar

CoRL 2018 PAC-Bayes Control: Synthesizing Controllers That Provably Generalize to Novel Environments Anirudha Majumdar, Maxwell Goldstein