145 citations · 404 across the 7 of their papers we have counts for
7 papers
Spherical Boltzmann machines: a solvable theory of learning and generation in energy-based models
Thomas Tulinski, Simona Cocco, Rémi Monasson +1
Energy-based models (EBMs) are flexible generative architectures inspired by statistical physics, but their learning and generative properties remain poorly understood. Here, we an…
Replica Theory of Spherical Boltzmann Machine Ensembles
Thomas Tulinski, Jorge Fernandez-De-Cossio-Diaz, Simona Cocco +1
Training in machine learning generally consists in finding one model, whose parameters minimize a data-dependent loss. Yet, empirical work shows that ensemble learning, an approach…
Cross-talk and transitions between multiple spatial maps in an attractor neural network model of the hippocampus: phase diagram (I)
Rémi Monasson, Sophie Rosay
We study the stable phases of an attractor neural network model, with binary units, for hippocampal place cells encoding 1D or 2D spatial maps or environments. Using statistical me…
From principal component to direct coupling analysis of coevolution in proteins: Low-eigenvalue modes are needed for structure prediction
Simona Cocco, Remi Monasson, Martin Weigt
Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those ar…
Reconstructing a Random Potential from its Random Walks
Simona Cocco, Remi Monasson
The problem of how many trajectories of a random walker in a potential are needed to reconstruct the values of this potential is studied. We show that this problem can be solved by…
A variational description of the ground state structure in random satisfiability problems
Giulio Biroli, Remi Monasson, Martin Weigt
A variational approach to finite connectivity spin-glass-like models is developed and applied to describe the structure of optimal solutions in random satisfiability problems. Our…