3 papers
cond-mat.stat-mech2026
Learning Cole-Hopf Coordinates for Stochastic Growth Dynamics: the KPZ class
Lorenzo Mensi, Simone Cuonzo, Maria Chiara Angelini +3
Inferring effective equations from observations of nonlinear stochastic processes is challenging because individual trajectories are noisy realizations, while the relevant physical…
cond-mat.dis-nn2026
Neural Renormalization Group Flow for Percolation
Anaclara Alvez, Luca Camagna, Sergio Chibbaro +4
Machine learning offers a possible route to data-driven real-space renormalization when the relevant observables are nonlocal and difficult to prescribe explicitly. We explore this…
cond-mat.dis-nn2026
Learning and extrapolating scale-invariant processes
Anaclara Alvez-Canepa, Cyril Furtlehner, François P. Landes
Machine Learning (ML) has deeply changed some fields recently, like Language and Vision and we may expect it to be relevant also to the analysis of of complex systems. Here we want…