3 papers
hep-lat2025
Exploring Generative Networks for Manifolds with Non-Trivial Topology
Shiyang Chen, Gert Aarts, Biagio Lucini
The expressive power of neural networks in modelling non-trivial distributions can in principle be exploited to bypass topological freezing and critical slowing down in simulations…
hep-lat2025
Topological Data Analysis of Abelian Magnetic Monopoles in Gauge Theories
Xavier Crean, Jeffrey Giansiracusa, Biagio Lucini
Motivated by recent literature on the possible existence of a second higher-temperature phase transition in Quantum Chromodynamics, we revisit the proposal that colour confinement…
hep-lat2024
Random Matrix Theory for Stochastic Gradient Descent
Chanju Park, Matteo Favoni, Biagio Lucini +1
Investigating the dynamics of learning in machine learning algorithms is of paramount importance for understanding how and why an approach may be successful. The tools of physics a…