265 citations · 2.3k across the 48 of their papers we have counts for
4 papers · 1 filter
'Place-cell' emergence and learning of invariant data with restricted Boltzmann machines: breaking and dynamical restoration of continuous symmetries in the weight space
Moshir Harsh, Jérôme Tubiana, Simona Cocco +1
Distributions of data or sensory stimuli often enjoy underlying invariances. How and to what extent those symmetries are captured by unsupervised learning methods is a relevant que…
Inference of compressed Potts graphical models
Francesca Rizzato, Alice Coucke, Eleonora de Leonardis +4
We consider the problem of inferring a graphical Potts model on a population of variables, with a non-uniform number of Potts colors (symbols) across variables. This inverse Potts…
Adaptive Cluster Expansion for Ising spin models
Simona Cocco, Giancarlo Croce, Francesco Zamponi
We propose an algorithm to obtain numerically approximate solutions of the direct Ising problem, that is, to compute the free energy and the equilibrium observables of spin systems…
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins
Jérôme Tubiana, Simona Cocco, Rémi Monasson
A Restricted Boltzmann Machine (RBM) is an unsupervised machine-learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relev…