activity
20162022
most citedComputational protein design with evolutionary-based and physics-inspired modeling: current and future synergies

37 citations · 37 across the 2 of their papers we have counts for

collaborators

7 papers

physics.bio-ph2022★ 37 cited

Computational protein design with evolutionary-based and physics-inspired modeling: current and future synergies

Cyril Malbranke, David Bikard, Simona Cocco +2

Computational protein design facilitates discovery of novel proteins with prescribed structure and functionality. Exciting designs were recently reported using novel data-driven me…

cond-mat.dis-nn2019

'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…

cond-mat.stat-mech2019

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…

cs.LG2019

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…

q-bio.QM2018

Learning protein constitutive motifs from sequence data

Jérôme Tubiana, Simona Cocco, Rémi Monasson

Statistical analysis of evolutionary-related protein sequences provides insights about their structure, function, and history. We show that Restricted Boltzmann Machines (RBM), des…

physics.data-an2017

Statistical Physics and Representations in Real and Artificial Neural Networks

Simona Cocco, Rémi Monasson, Lorenzo Posani +2

This document presents the material of two lectures on statistical physics and neural representations, delivered by one of us (R.M.) at the Fundamental Problems in Statistical Phys…