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Maximum likelihood / Likelihood function / Boltzmann machine / Score / Kullback–Leibler divergence / Estimation theory / Statistics / Statistical theory


Under review as a conference paper at ICLRU NDERSTANDING M INIMUM P ROBABILITY F LOW U NDER VARIOUS K INDS OF DYNAMICS FOR
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Document Date: 2014-12-30 23:07:00

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Company

LG / MPF / MIT Press / CSL / /

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Event

FDA Phase / /

Facility

Engineering University of Guelph Guelph / /

IndustryTerm

contrastive divergence training algorithm / energy function / statistical mechanical systems / unsupervised neural network / Information processing / deep belief networks / average energy / free energy / energy-based model / energy-based models / incomprehensible transition operator / dynamical systems / learning algorithm / deep neural networks / energy / /

MusicAlbum

PCD / /

Organization

Redwood Centre for Theoretical Neuroscience / National Park Service / Engineering University of Guelph Guelph / MIT / Buchman & Graham W. Taylor School / /

Person

Ruslan / Murray / Geoffrey E. Using / Michael R. Minimum / Daniel Jiwoong Im / Ethan Buchman / /

Position

Statistician / /

Product

DYNAMICS FOR RBM / /

PublishedMedium

Machine Learning / Journal of Machine Learning Research / /

Technology

Neuroscience / neural network / artificial intelligence / unsupervised algorithm / Minimum Probability Flow learning algorithm / machine learning / contrastive divergence training algorithm / /

URL

http /

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