Srinivasa, Siddhartha

22 publications

CoRL 2025 ATK: Automatic Task-Driven Keypoint Selection for Robust Policy Learning Yunchu Zhang, Shubham Mittal, Zhengyu Zhang, Liyiming Ke, Siddhartha Srinivasa, Abhishek Gupta

CVPR 2025 Causal Composition Diffusion Model for Closed-Loop Traffic Generation Haohong Lin, Xin Huang, Tung Phan, David Hayden, Huan Zhang, Ding Zhao, Siddhartha Srinivasa, Eric Wolff, Hongge Chen

ICML 2025 DriveGPT: Scaling Autoregressive Behavior Models for Driving Xin Huang, Eric M Wolff, Paul Vernaza, Tung Phan-Minh, Hongge Chen, David S Hayden, Mark Edmonds, Brian Pierce, Xinxin Chen, Pratik Elias Jacob, Xiaobai Chen, Chingiz Tairbekov, Pratik Agarwal, Tianshi Gao, Yuning Chai, Siddhartha Srinivasa

ICML 2025 Generative Data Mining with Longtail-Guided Diffusion David S Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M Wolff, Siddhartha Srinivasa

CoRL 2025 Long Range Navigator (LRN): Extending Robot Planning Horizons Beyond Metric Maps Matt Schmittle, Rohan Baijal, Nathan Hatch, Rosario Scalise, Mateo Guaman Castro, Sidharth Talia, Khimya Khetarpal, Byron Boots, Siddhartha Srinivasa

JMLR 2025 On Global and Local Convergence of Iterative Linear Quadratic Optimization Algorithms for Discrete Time Nonlinear Control Vincent Roulet, Siddhartha Srinivasa, Maryam Fazel, Zaid Harchaoui

CoRL 2025 VLM-AD: End-to-End Autonomous Driving Through Vision-Language Model Supervision Yi Xu, Yuxin Hu, Zaiwei Zhang, Gregory P. Meyer, Siva Karthik Mustikovela, Siddhartha Srinivasa, Eric M. Wolff, Xin Huang

ICLR 2024 CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning Liyiming Ke, Yunchu Zhang, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta

ICLR 2023 Git Re-Basin: Merging Models Modulo Permutation Symmetries Samuel Ainsworth, Jonathan Hayase, Siddhartha Srinivasa

CoRL 2023 Towards General Single-Utensil Food Acquisition with Human-Informed Actions Ethan Kroll Gordon, Amal Nanavati, Ramya Challa, Bernie Hao Zhu, Taylor Annette Kessler Faulkner, Siddhartha Srinivasa

NeurIPSW 2022 Real World Offline Reinforcement Learning with Realistic Data Source Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar

NeurIPSW 2022 Real World Offline Reinforcement Learning with Realistic Data Source Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar

L4DC 2021 Faster Policy Learning with Continuous-Time Gradients Samuel Ainsworth, Kendall Lowrey, John Thickstun, Zaid Harchaoui, Siddhartha Srinivasa

CoRL 2021 Influencing Behavioral Attributions to Robot Motion During Task Execution Nick Walker, Christoforos Mavrogiannis, Siddhartha Srinivasa, Maya Cakmak

CoRL 2020 Amodal 3D Reconstruction for Robotic Manipulation via Stability and Connectivity William Agnew, Christopher Xie, Aaron Walsman, Octavian Murad, Yubo Wang, Pedro Domingos), Siddhartha Srinivasa

L4DC 2020 Lyceum: An Efficient and Scalable Ecosystem for Robot Learning Colin Summers, Kendall Lowrey, Aravind Rajeswaran, Siddhartha Srinivasa, Emanuel Todorov

CoRL 2020 Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled Intersections Junha Roh, Christoforos Mavrogiannis, Rishabh Madan, Dieter Fox, Siddhartha Srinivasa

ICML 2019 Iterative Linearized Control: Stable Algorithms and Complexity Guarantees Vincent Roulet, Siddhartha Srinivasa, Dmitriy Drusvyatskiy, Zaid Harchaoui

NeurIPS 2019 Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation Samuel Ainsworth, Matt Barnes, Siddhartha Srinivasa

ICML 2018 Recurrent Predictive State Policy Networks Ahmed Hefny, Zita Marinho, Wen Sun, Siddhartha Srinivasa, Geoffrey Gordon

NeurIPS 2017 Near-Optimal Edge Evaluation in Explicit Generalized Binomial Graphs Sanjiban Choudhury, Shervin Javdani, Siddhartha Srinivasa, Sebastian Scherer

AISTATS 2009 Inverse Optimal Heuristic Control for Imitation Learning Nathan Ratliff, Brian Ziebart, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha Srinivasa