Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …

One challenge of physics is to explain how collective properties arise from microscopic
interactions. Indeed, interactions form the building blocks of almost all physical theories and …

To improve the storage capacity of the Hopfield model, we develop a version of the
dreaming algorithm that perpetually reinforces the patterns to be stored (as in the Hebb …

In this paper, we solve the inverse problem for the cubic mean-field Ising model. Starting
from configuration data generated according to the distribution of the model, we reconstruct …

Stochastic neural networks are a prototypical computational device able to build a
probabilistic representation of an ensemble of external stimuli. Building on the relationship …

The system under consideration comprises Ising spins, a homogeneous magnetic field, and
a constant two-spin interaction, augmented by a constant three-spin interaction term …

The ability of processing and storing information is considered a characteristic trait of
intelligent systems. In biological neural networks, learning is strongly believed to take place …