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Found 5 papers, 1 papers with code
Pattern reconstruction with restricted Boltzmann machines
We identify an effective energy function describing the zero-temperature landscape on the visible units and depending only on the tail behaviour of the hidden layer prior distribution.
Universal approximation of credit portfolio losses using Restricted Boltzmann Machines
We introduce a new portfolio credit risk model based on Restricted Boltzmann Machines (RBMs), which are stochastic neural networks capable of universal approximation of loss distributions.
Minimax formula for the replica symmetric free energy of deep restricted Boltzmann machines
We study the free energy of a most used deep architecture for restricted Boltzmann machines, where the layers are disposed in series.
Phase Diagram of Restricted Boltzmann Machines and Generalised Hopfield Networks with Arbitrary Priors
Restricted Boltzmann Machines are described by the Gibbs measure of a bipartite spin glass, which in turn corresponds to the one of a generalised Hopfield network.
Phase transitions in Restricted Boltzmann Machines with generic priors
We study Generalised Restricted Boltzmann Machines with generic priors for units and weights, interpolating between Boolean and Gaussian variables.
