Conference icon

Conference

Multi-task Gaussian process models for biomedical applications

Abstract:

Gaussian process (GP) models are a flexible means of performing non-parametric Bayesian regression. However, the majority of existing work using GP models in healthcare data is defined for univariate output time-series, denoted as single-task GPs (STGP). Here, we investigate how GPs could be used to model multiple correlated univariate physiological time-series simultaneously. The resulting multi-task GP (MTGP) framework can learn the correlation within multiple signals even though they might...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1109/BHI.2014.6864410

Authors


Durichen, R More by this author
Pimentel, MAF More by this author
More by this author
Institution:
University of Oxford
Department:
Oxford, MSD, NDORMS, CSM
Schweikard, A More by this author
Clifton, DA More by this author
Royal Academy of Engineering Research Fellowship More from this funder
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Pages:
492-495
Publication date:
2014-01-05
DOI:
URN:
uuid:22f72d57-8104-4ca7-ade9-54970b50c133
Source identifiers:
484271
Local pid:
pubs:484271
ISBN:
9781479921317

Terms of use


Metrics



If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP