Sherrington–Kirkpatrick models artificial neurons stochastic optimization local minima weight neurons neural networks
Stochastic neural networks originating from  Sherrington–Kirkpatrick models  are a type of artificial neural network built by introducing random variations into the network, either by giving the network's artificial neurons stochastic transfer functions, or by giving them stochastic weights. This makes them useful tools for optimization problems, since the random fluctuations help the network escape from local minima. Stochastic neural networks trained using a Bayesian approach are known as Bayesian neural networks.
