13 citations · 27 across the 5 of their papers we have counts for
5 papers
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…
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…
Class Imbalance in Anomaly Detection: Learning from an Exactly Solvable Model
F. S. Pezzicoli, V. Ros, F. P. Landes +1
Class imbalance (CI) is a longstanding problem in machine learning, slowing down training and reducing performances. Although empirical remedies exist, it is often unclear which on…
Dynamical Facilitation Governs the Equilibration Dynamics of Glasses
Rahul N. Chacko, François P. Landes, Giulio Biroli +3
Convincing evidence of domain growth in the heating of ultrastable glasses suggests that the equilibration dynamics of super-cooled liquids could be driven by a nucleation and grow…
Rotation-equivariant Graph Neural Networks for Learning Glassy Liquids Representations
Francesco Saverio Pezzicoli, Guillaume Charpiat, François P. Landes
The difficult problem of relating the static structure of glassy liquids and their dynamics is a good target for Machine Learning, an approach which excels at finding complex patte…