2 papers
hep-lat2024
Generating configurations of increasing lattice size with machine learning and the inverse renormalization group
Dimitrios Bachtis
We review recent developments of machine learning algorithms pertinent to the inverse renormalization group, which was originally established as a generative numerical method by Ro…
cs.LG2024
Cascade of phase transitions in the training of Energy-based models
Dimitrios Bachtis, Giulio Biroli, Aurélien Decelle +1
In this paper, we investigate the feature encoding process in a prototypical energy-based generative model, the Restricted Boltzmann Machine (RBM). We start with an analytical inve…