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Found 3 papers, 1 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.
Multilevel Monte Carlo for quantum mechanics on a lattice
This paper discusses hierarchical sampling methods to tame this growth in autocorrelations.
High Energy Physics - Lattice Numerical Analysis Numerical Analysis Computational Physics 81-08, 81T25, 65Y20, 60J22 F.2; J.2
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.
