3 papers
cond-mat.dis-nn2026
Transition path sampling in Ising models on heterogeneous graphs
Riccardo Cipolloni, Federico Ricci-Tersenghi, Francesco Zamponi
Activated transitions have rates that are often exponentially small in system size. Extracting the associated activation barriers is challenging in practice, especially in the deep…
cond-mat.dis-nn2026
Dreaming improves memorization in a Hopfield model with bounded synaptic strength
Enzo Marinari, Saverio Rossi, Francesco Zamponi
The Hopfield model provides a paradigmatic framework for associative memory. Its classical implementation, based on the Hebbian learning rule, suffers from catastrophic forgetting:…
cond-mat.dis-nn2024
Unlearning regularization for Boltzmann Machines
Enrico Ventura, Simona Cocco, Rémi Monasson +1
Boltzmann Machines (BMs) are graphical models with interconnected binary units, employed for the unsupervised modeling of data distributions. When trained on real data, BMs show th…