Wake-sleep algorithm
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The wake-sleep algorithm is an unsupervised learning algorithm for deep generative models, especially Helmholtz Machines. The algorithm is similar to the expectation-maximization algorithm, and optimi
Layers of the neural network. R, G are weights used by the wake-sleep algorithm to modify data inside the layers.
Bayesian inference
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Bayesian inference is a method of statistical inference in which Bayes' theorem is used to calculate a probability of a hypothesis, given prior evidence, and update it as more information becomes avai
Wake-sleep algorithm
…gradually more abstract representations. Between each pair of layers are two sets of weights: Recognition weights, which define how representations are inferred from data, and generative weights, which define how these representations relate to data. Training consists of two phases – the “wake” phase and the…
Example results for archaeology example. This simulation was generated using c=15.2.