nuloVile review some recent rigorous results in the theory of neural networks, and in particular on the thermodynamic properties of the Hopfield model. In this context, the model is treated as a Cllrie-Weiss model with random interact, ions and large deviation t,echniques are applied, The tractability of the random interactions depends strongly on how the number, M. of stored patterns scales with the size N. of the system
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d...
Standard large deviation estimates or the use of the Hubbard-Stratonovich transformation reduce the ...
We analyze the storage capacity of the Hopfield model with spatially correlated patterns ¸ i (i.e....
We review some recent rigorous results in the theory of neural networks, and in particular on the th...
We review some recent rigorous results in the theory of neural networks, and in particular on the th...
We survey the statistical mechanics approach to the analysis of neural networks of the Hopfield type...
We study the Hopfield model of an autoassociative memory on a random graph on N vertices where the p...
We investigate the fluctuations of the order parameter in the Hopfield model of spin glasses and neu...
We prove a large deviation principle for the finite dimensional marginals of the Gibbs distribution ...
We study the Hopfield model of an autoassociative memory on a random graph on N vertices where the p...
We consider a generalization of the Hopfield model, where the entries of patterns are Gaussian and d...
We prove the almost sure convergence to zero of the fluctuations of the free energy, resp. local fre...
We first show the self-averaging property in the sense of almost sure convergence for the free energ...
102 pagesWe study the asymptotic behaviour for asymmetric neuronal dynamics in a network of Hopfield...
textabstractStochastic binary Hopfield models are viewed from the angle of statistical mechanics. Af...
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d...
Standard large deviation estimates or the use of the Hubbard-Stratonovich transformation reduce the ...
We analyze the storage capacity of the Hopfield model with spatially correlated patterns ¸ i (i.e....
We review some recent rigorous results in the theory of neural networks, and in particular on the th...
We review some recent rigorous results in the theory of neural networks, and in particular on the th...
We survey the statistical mechanics approach to the analysis of neural networks of the Hopfield type...
We study the Hopfield model of an autoassociative memory on a random graph on N vertices where the p...
We investigate the fluctuations of the order parameter in the Hopfield model of spin glasses and neu...
We prove a large deviation principle for the finite dimensional marginals of the Gibbs distribution ...
We study the Hopfield model of an autoassociative memory on a random graph on N vertices where the p...
We consider a generalization of the Hopfield model, where the entries of patterns are Gaussian and d...
We prove the almost sure convergence to zero of the fluctuations of the free energy, resp. local fre...
We first show the self-averaging property in the sense of almost sure convergence for the free energ...
102 pagesWe study the asymptotic behaviour for asymmetric neuronal dynamics in a network of Hopfield...
textabstractStochastic binary Hopfield models are viewed from the angle of statistical mechanics. Af...
We introduce a form of the Hopfield model that is able to store an increasing number of biased i.i.d...
Standard large deviation estimates or the use of the Hubbard-Stratonovich transformation reduce the ...
We analyze the storage capacity of the Hopfield model with spatially correlated patterns ¸ i (i.e....