| Gaussian processes for time-series modelling. | |
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MedLine Citation:
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PMID: 23277607 Owner: NLM Status: PubMed-not-MEDLINE |
Abstract/OtherAbstract:
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In this paper, we offer a gentle introduction to Gaussian processes for time-series data analysis. The conceptual framework of Bayesian modelling for time-series data is discussed and the foundations of Bayesian non-parametric modelling presented for Gaussian processes. We discuss how domain knowledge influences design of the Gaussian process models and provide case examples to highlight the approaches. |
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Authors:
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S Roberts; M Osborne; M Ebden; S Reece; N Gibson; S Aigrain |
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Publication Detail:
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Type: Journal Article Date: 2012-12-31 |
Journal Detail:
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Title: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Volume: 371 ISSN: 1364-503X ISO Abbreviation: Philos Trans A Math Phys Eng Sci Publication Date: 2013 Feb |
Date Detail:
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Created Date: 2013-01-01 Completed Date: 2013-03-07 Revised Date: 2013-04-24 |
Medline Journal Info:
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Nlm Unique ID: 101133385 Medline TA: Philos Trans A Math Phys Eng Sci Country: England |
Other Details:
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Languages: eng Pagination: 20110550 Citation Subset: - |
Affiliation:
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Department of Engineering Science, University of Oxford, Oxford OX1 3PU, UK. sjrob@robots.ox.ac.uk |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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