Search Results for author:
Found 2 papers, 0 papers with code
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse
Crucially, these models allow for the direct estimation of the free energy at a given point in parameter space.
Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models
In this work, we demonstrate that applying deep generative machine learning models for lattice field theory is a promising route for solving problems where Markov Chain Monte Carlo (MCMC) methods are problematic.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
