منابع مشابه
Varieties of Helmholtz Machine
The Helmholtz machine is a new unsupervised learning architecture that uses top-down connections to build probability density models of input and bottom-up connections to build inverses to those models. The wake-sleep learning algorithm for the machine involves just the purely local delta rule. This paper suggests a number of different varieties of Helmholtz machines, each with its own strength...
متن کاملThe Helmholtz machine
Discovering the structure inherent in a set of patterns is a fundamental aim of statistical inference or learning. One fruitful approach is to build a parameterized stochastic generative model, independent draws from which are likely to produce the patterns. For all but the simplest generative models, each pattern can be generated in exponentially many ways. It is thus intractable to adjust the...
متن کاملSpiking neuron network Helmholtz machine
An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in...
متن کاملA Coupled Helmholtz Machine for PCA
In this letter we present a coupled Helmholtz machine for principal component analysis (PCA), where sub-machines are related through sharing some latent variables and associated weights. Then, we present a wake-sleep PCA algorithm for training the coupled Helmholtz machine, showing that the algorithm iteratively determines principal eigenvectors of a data covariance matrix without any rotationa...
متن کاملRecurrent Sampling Models for the Helmholtz Machine
Many recent analysis-by-synthesis density estimation models of cortical learning and processing have made the crucial simplifying assumption that units within a single layer are mutually independent given the states of units in the layer below or the layer above. In this article, we suggest using either a Markov random field or an alternative stochastic sampling architecture to capture explicit...
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ژورنال
عنوان ژورنال: Neural Networks
سال: 1996
ISSN: 0893-6080
DOI: 10.1016/s0893-6080(96)00009-3