Classifying States of the Hopfield Network with Improved Accuracy, Generalization, and Interpretability

Hayden McAlister, Anthony Robins, Lech Szymanski

We extend the existing work on Hopfield network state classification, employing more complex models that remain interpretable, such as densely-connected feed-forward deep neural ne…