Higher-order interactions in statistical physics and machine learning: A model-independent solution to the inverse problem at equilibrium

no code implementations • 10 Jun 2020 • Sjoerd Viktor Beentjes, Ava Khamseh

The problem of inferring pair-wise and higher-order interactions in complex systems involving large numbers of interacting variables, from observational data, is fundamental to many fields.

Machine learning determination of dynamical parameters: The Ising model case

1 code implementation • 26 Oct 2018 • Guido Cossu, Luigi Del Debbio, Tommaso Giani, Ava Khamseh, Michael Wilson

We train a set of Restricted Boltzmann Machines (RBMs) on one- and two-dimensional Ising spin configurations at various values of temperature, generated using Monte Carlo simulations.

Computational Physics Statistical Mechanics High Energy Physics - Lattice