Factoring variations in natural images with deep Gaussian mixture models

Advances in Neural Information Processing Systems

Volumn 4, Issue January, 2014, Pages 3518-3526

  Van Den Oord, Aäron ^a   Schrauwen, Benjamin ^a  

^a GHENT UNIVERSITY   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMMUNICATION CHANNELS (INFORMATION THEORY); INFORMATION SCIENCE; LEARNING SYSTEMS; OBJECT RECOGNITION; UNSUPERVISED LEARNING;

CURRENT PROBLEMS; DENSITY ESTIMATION; GAUSSIAN MIXTURE MODEL; GENERATIVE MODEL; PARAMETRIZATIONS; STATE OF THE ART; T-MIXTURE MODELS; UNSUPERVISED LEARNING METHOD;

GAUSSIAN DISTRIBUTION;

EID: 84937926152     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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