2 papers
cond-mat.stat-mech2026
Learning and Testing Inverse Statistical Problems For Interacting Systems Undergoing Phase Transition
Stefano Bae, Dario Bocchi, Luca Maria Del Bono +1
Inverse problems arise in situations where data is available, but the underlying model is not. It can therefore be necessary to infer the parameters of the latter starting from the…
cond-mat.dis-nn2025
A Very Effective and Simple Diffusion Reconstruction for the Diluted Ising Model
Stefano Bae, Enzo Marinari, Federico Ricci-Tersenghi
Diffusion-based generative models are machine learning models that use diffusion processes to learn the probability distribution of high-dimensional data. In recent years, they hav…