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Deep Forward and Inverse Perceptual Models for Tracking and Prediction.

A. Lambert, A. Shaban, A. Raj, Z. Liu, and B. Boots. ICRA, page 675-682. IEEE, (2018)

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Learning predictive models of a depth camera & manipulator from raw execution traces.B. Boots, A. Byravan, and D. Fox. ICRA, page 4021-4028. IEEE, (2014)Online Instrumental Variable Regression with Applications to Online Linear System Identification.A. Venkatraman, W. Sun, M. Hebert, J. Bagnell, and B. Boots. AAAI, page 2101-2107. AAAI Press, (2016)Closing the learning-planning loop with predictive state representations.B. Boots, S. Siddiqi, and G. Gordon. I. J. Robotics Res., 30 (7): 954-966 (2011)Learning from Conditional Distributions via Dual Kernel Embeddings.B. Dai, N. He, Y. Pan, B. Boots, and L. Song. CoRR, (2016)Continuous-Time Gaussian Process Motion Planning via Probabilistic Inference.M. Mukadam, J. Dong, X. Yan, F. Dellaert, and B. Boots. CoRR, (2017)STEAP: simultaneous trajectory estimation and planning.M. Mukadam, J. Dong, F. Dellaert, and B. Boots. CoRR, (2018)Model-Based Imitation Learning with Accelerated Convergence.C. Cheng, X. Yan, E. Theodorou, and B. Boots. CoRR, (2018)Hilbert Space Embeddings of Predictive State Representations.B. Boots, G. Gordon, and A. Gretton. CoRR, (2013)Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning.Y. Pan, C. Cheng, K. Saigol, K. Lee, X. Yan, E. Theodorou, and B. Boots. CoRR, (2017)Robust Learning of Tactile Force Estimation through Robot Interaction.B. Sundaralingam, A. Lambert, A. Handa, B. Boots, T. Hermans, S. Birchfield, N. Ratliff, and D. Fox. ICRA, page 9035-9042. IEEE, (2019)

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Deep Forward and Inverse Perceptual Models for Tracking and Prediction.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Deep Forward and Inverse Perceptual Models for Tracking and Prediction.

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Deep Forward and Inverse Perceptual Models for Tracking and Prediction.