An approximate inference with Gaussian process to latent functions from uncertain data

Neurocomputing

Volumn 74, Issue 11, 2011, Pages 1945-1955

  Dallaire, Patrick ^a   Besse, Camille ^a   Chaib draa, Brahim ^a  

^a UNIVERSITÉ LAVAL   (Canada)

Author keywords

Data uncertainty; Dynamical systems; Gaussian processes; Supervised learning

Indexed keywords

APPROXIMATE INFERENCE; COVARIANCE FUNCTION; DATA UNCERTAINTY; GAUSSIAN PROCESSES; INPUT-OUTPUT; LATENT FUNCTION; LEARNING TASKS; MEAN SQUARED ERROR; POSTERIOR DISTRIBUTIONS; SYNTHETIC PROBLEM; UNCERTAIN DATAS;

COVARIANCE MATRIX; DISTRIBUTION FUNCTIONS; DYNAMICAL SYSTEMS; GAUSSIAN NOISE (ELECTRONIC); SUPERVISED LEARNING;

GAUSSIAN DISTRIBUTION;

ARTICLE; COVARIANCE; INFERENTIAL STATISTICS; MACHINE LEARNING; MATHEMATICAL COMPUTING; MEASUREMENT ERROR; NORMAL DISTRIBUTION; PRIORITY JOURNAL; PROBLEM BASED LEARNING; UNCERTAINTY;

EID: 79956060333     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2010.09.024     Document Type: Article

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