Gaussian process latent force models for learning and stochastic control of physical systems

Särkkä, S., Álvarez, M.A. and Lawrence, N.D. orcid.org/0000-0001-9258-1030 (2018) Gaussian process latent force models for learning and stochastic control of physical systems. IEEE Transactions on Automatic Control. ISSN 0018-9286

Abstract

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Authors/Creators:
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Keywords: Machine learning; Stochastic optimal control; Stochastic systems; System identification; Kalman filtering
Dates:
  • Accepted: 12 September 2018
  • Published (online): 8 October 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
FunderGrant number
EUROPEAN COMMISSION - FP6/FP7BIOPREDYN - 289434
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL (EPSRC)EP/N014162/1
Depositing User: Symplectic Sheffield
Date Deposited: 09 Oct 2018 14:57
Last Modified: 10 Oct 2018 14:10
Published Version: https://doi.org/10.1109/TAC.2018.2874749
Status: Published online
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/TAC.2018.2874749

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