Sanjiban Choudhury

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i10-rodyklė	51	42

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Sebastian SchererAssociate Research Professor, Carnegie Mellon UniversityPatvirtintas el. paštas andrew.cmu.edu
Siddhartha SrinivasaProfessor, University of WashingtonPatvirtintas el. paštas cs.washington.edu
J. Andrew BagnellCarnegie Mellon UniversityPatvirtintas el. paštas ri.cmu.edu
Gilwoo LeeUniversity of WashingtonPatvirtintas el. paštas cs.washington.edu
Aditya MandalikaPhD Student, Computer Science and Engineering, University of WashingtonPatvirtintas el. paštas cs.washington.edu
Brian HouUniversity of WashingtonPatvirtintas el. paštas cs.uw.edu
Mohak BhardwajUniversity of WashingtonPatvirtintas el. paštas cs.washington.edu
Sankalp AroraStudent at Robotics InstitutePatvirtintas el. paštas andrew.cmu.edu
Sanjiv SinghResearch Professor, Carnegie Mellon UniversityPatvirtintas el. paštas cmu.edu
Rogerio BonattiSenior Researcher, MicrosoftPatvirtintas el. paštas microsoft.com
Wenshan WangCarnegie Mellon UniversityPatvirtintas el. paštas andrew.cmu.edu
Debadeepta DeyDistinguished Researcher, DataRobotPatvirtintas el. paštas debadeepta.com
Ashish KapoorCEO and Chief Scientist, Scaled FoundationsPatvirtintas el. paštas scaledfoundations.ai
Oren SalzmanTechnion-Israel Institute of TechnologyPatvirtintas el. paštas cs.technion.ac.il
Vishal DugarRobotics Institute, Carnegie Mellon UniversityPatvirtintas el. paštas andrew.cmu.edu
Byron BootsAssociate Professor, University of WashingtonPatvirtintas el. paštas cs.washington.edu
Jonathan GammellAssistant Professor, Queen's UniversityPatvirtintas el. paštas queensu.ca
Timothy D BarfootProfessor, University of Toronto (UTIAS)Patvirtintas el. paštas utoronto.ca
Guilherme A. S. PereiraProfessor of Robotics, West Virginia UniversityPatvirtintas el. paštas mail.wvu.edu
Stephen NuskePatvirtintas el. paštas aquabyte.ai

Stebėti

Sanjiban Choudhury

Assistant Professor, Cornell

Patvirtintas el. paštas cornell.edu - Pagrindinis puslapis

Machine Learning Reinforcement Learning Imitation Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Imitation learning as f-divergence minimization L Ke, S Choudhury, M Barnes, W Sun, G Lee, S Srinivasa Algorithmic Foundations of Robotics XIV: Proceedings of the Fourteenth …, 2021	177	2021
Regionally accelerated batch informed trees (rabit*): A framework to integrate local information into optimal path planning S Choudhury, JD Gammell, TD Barfoot, SS Srinivasa, S Scherer 2016 IEEE International Conference on Robotics and Automation (ICRA), 4207-4214, 2016	134	2016
Learning Heuristic Search via Imitation M Bhardwaj, S Choudhury, S Scherer Conference on Robot Learning (CoRL), 2017	106	2017
Autonomous aerial cinematography in unstructured environments with learned artistic decision‐making R Bonatti, W Wang, C Ho, A Ahuja, M Gschwindt, E Camci, E Kayacan, ... Journal of Field Robotics 37 (4), 606-641, 2020	105	2020
Towards a robust aerial cinematography platform: Localizing and tracking moving targets in unstructured environments R Bonatti, C Ho, W Wang, S Choudhury, S Scherer 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019	101	2019
Data-driven planning via imitation learning S Choudhury, M Bhardwaj, S Arora, A Kapoor, G Ranade, S Scherer, ... The International Journal of Robotics Research 37 (13-14), 1632-1672, 2018	96	2018
MuSHR: A low-cost, open-source robotic racecar for education and research SS Srinivasa, P Lancaster, J Michalove, M Schmittle, C Summers, ... arXiv preprint arXiv:1908.08031, 2019	91	2019
Of moments and matching: A game-theoretic framework for closing the imitation gap G Swamy, S Choudhury, JA Bagnell, S Wu International Conference on Machine Learning, 10022-10032, 2021	79	2021
Lego: Leveraging experience in roadmap generation for sampling-based planning R Kumar, A Mandalika, S Choudhury, S Srinivasa 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019	77	2019
Generalized Lazy Search for Robot Motion Planning: Interleaving Search and Edge Evaluation via Event-based Toggles A Mandalika, S Choudhury, O Salzman, S Srinivasa International Conference on Automated Planning and Scheduling (ICAPS), 2019	77	2019
Feedback in imitation learning: The three regimes of covariate shift J Spencer, S Choudhury, A Venkatraman, B Ziebart, JA Bagnell arXiv preprint arXiv:2102.02872, 2021	75	2021
Autonomous exploration and motion planning for an unmanned aerial vehicle navigating rivers S Nuske, S Choudhury, S Jain, A Chambers, L Yoder, S Scherer, ... Journal of Field Robotics 32 (8), 1141-1162, 2015	75	2015
Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming R Bonatti, Y Zhang, S Choudhury, W Wang, S Scherer International Symposium of Experimental Robotics (ISER), 2018	73	2018
Sparse tangential network (SPARTAN): Motion planning for micro aerial vehicles H Cover, S Choudhury, S Scherer, S Singh 2013 IEEE International Conference on Robotics and Automation, 2820-2825, 2013	63	2013
RRT*-AR: Sampling-based alternate routes planning with applications to autonomous emergency landing of a helicopter S Choudhury, S Scherer, S Singh 2013 IEEE International Conference on Robotics and Automation, 3947-3952, 2013	59	2013
Learning from interventions: Human-robot interaction as both explicit and implicit feedback J Spencer, S Choudhury, M Barnes, M Schmittle, M Chiang, P Ramadge, ... 16th robotics: science and systems, RSS 2020, 2020	58	2020
Bayesian Policy Optimization for Model Uncertainty G Lee, B Hou, A Mandalika, J Lee, SS Srinivasa International Conference on Learning Representations (ICLR), 2019	55	2019
Learning to gather information via imitation S Choudhury, A Kapoor, G Ranade, D Dey 2017 IEEE international conference on robotics and automation (ICRA), 908-915, 2017	40	2017
Expert intervention learning: An online framework for robot learning from explicit and implicit human feedback J Spencer, S Choudhury, M Barnes, M Schmittle, M Chiang, P Ramadge, ... Autonomous Robots, 1-15, 2022	39	2022
Blending mpc & value function approximation for efficient reinforcement learning M Bhardwaj, S Choudhury, B Boots arXiv preprint arXiv:2012.05909, 2020	38	2020

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