| Deeply aggrevated: Differentiable imitation learning for sequential prediction W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell International conference on machine learning, 3309-3318, 2017 | 231 | 2017 |
| Improving multi-step prediction of learned time series models A Venkatraman, M Hebert, JA Bagnell AAAI Conference on Artificial Intelligence, 2015 | 211 | 2015 |
| Perceiving, Learning, and Exploiting Object Affordances for Autonomous Pile Manipulation D Katz, A Venkatraman, M Kazemi, JA Bagnell, A Stentz Robotics Science and Systems, 2013 | 125 | 2013 |
| Autonomy infused teleoperation with application to brain computer interface controlled manipulation K Muelling, A Venkatraman, JS Valois, JE Downey, J Weiss, S Javdani, ... Autonomous Robots 41, 1401-1422, 2017 | 97 | 2017 |
| Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping JE Downey, JM Weiss, K Muelling, A Venkatraman, JS Valois, M Hebert, ... Journal of neuroengineering and rehabilitation 13 (1), 1-12, 2016 | 97 | 2016 |
| Autonomy infused teleoperation with application to BCI manipulation K Muelling, A Venkatraman, JS Valois, J Downey, J Weiss, S Javdani, ... arXiv preprint arXiv:1503.05451, 2015 | 67 | 2015 |
| Learning to filter with predictive state inference machines W Sun, A Venkatraman, B Boots, JA Bagnell International conference on machine learning, 1197-1205, 2016 | 57 | 2016 |
| Improved learning of dynamics models for control A Venkatraman, R Capobianco, L Pinto, M Hebert, D Nardi, JA Bagnell 2016 International Symposium on Experimental Robotics, 703-713, 2017 | 43 | 2017 |
| Predictive-state decoders: Encoding the future into recurrent networks A Venkatraman, N Rhinehart, W Sun, L Pinto, M Hebert, B Boots, K Kitani, ... Advances in Neural Information Processing Systems 30, 2017 | 42 | 2017 |
| Spatio-temporal matching for human pose estimation in video F Zhou, F De la Torre IEEE Transactions on Pattern Analysis and Machine Intelligence 38 (8), 1492-1504, 2016 | 31 | 2016 |
| 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 | 26 | 2021 |
| Online instrumental variable regression with applications to online linear system identification A Venkatraman, W Sun, M Hebert, J Bagnell, B Boots Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 19 | 2016 |
| Gradient boosting on stochastic data streams H Hu, W Sun, A Venkatraman, M Hebert, A Bagnell Artificial Intelligence and Statistics, 595-603, 2017 | 16 | 2017 |
| DATA AS DEMONSTRATOR with Applications to System Identification A Venkatraman, B Boots, M Hebert, JA Bagnell NIPS Autonomously Learning Robots Workshop, 2014 | 15 | 2014 |
| Inference Machines for Nonparametric Filter Learning A Venkatraman, W Sun, M Hebert, B Boots, JA Bagnell 25th International Joint Conference on Artificial Intelligence (IJCAI-16), 2016 | 7 | 2016 |
| Training Strategies for Time Series: Learning for Prediction, Filtering, and Reinforcement Learning A Venkatraman Carnegie Mellon University, 2017 | 3 | 2017 |
| Brain-Machine Interface Control of a Robotic Arm for Object Grasping is Improved With Computer-Vision Based Shared Control. CJ Tyler-Kabara EC, Downey J, Weiss J, Muelling K, Venkataraman A, Valois JS ... Neurosurgery 62, 233--233, 2015 | 3 | 2015 |
| A Novel Control Algorithm for Regulating the Tinting of Electrochromic Windows A Venkatraman, A Ram | 1 | 2005 |
| Systems and Methods Related to Controlling Autonomous Vehicle (s) JA Bagnell, S Choudhury, V Narayanan, A Venkatraman US Patent App. 17/522,031, 2023 | | 2023 |
| Training Strategies for Time Series: Learning for Filtering and Reinforcement Learning A Venkatraman Georgia Institute of Technology, 2016 | | 2016 |
J. Andrew BagnellCarnegie Mellon UniversityVerified email at ri.cmu.edu
