Representing the 2D Ising model with a Restricted Boltzmann Machine
The Restricted Boltzmann Machine is trained to represent the probability distribution of the 2D Ising Model. It is trained on data generated by the Metropolis-Hastings algorithm. The Kullback-Leibler divergence between the probability distributions is minimized using stochastic gradient descent and Gibb's sampling.
This code was used in a project completed with Dr. Ehsan Khatami