59 citations · 177 across the 14 of their papers we have counts for
14 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…
A High-Order Cumulant Extension of Quasi-Linkage Equilibrium
Kai S. Shimagaki, Jorge Fernandez-de-Cossio-Diaz, Mauro Pastore +3
A central question in evolutionary biology is how to quantitatively understand the dynamics of genetically diverse populations. Modeling the genotype distribution is challenging, a…
Disentangling representations in Restricted Boltzmann Machines without adversaries
Jorge Fernandez-de-Cossio-Diaz, Simona Cocco, Remi Monasson
A goal of unsupervised machine learning is to build representations of complex high-dimensional data, with simple relations to their properties. Such disentangled representations m…
Inferring metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy Approach with minimum information
Jose A. Pereiro-Morejón, Jorge Fernández-de-Cossio-Díaz, R. Mulet
We propose a new scheme to infer the metabolic fluxes of cell cultures in a chemostat. Our approach is based on the Maximum Entropy Principle and exploits the understanding of the…
Spin Glass Theory of Interacting Metabolic Networks
Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet
We cast the metabolism of interacting cells within a statistical mechanics framework considering both, the actual phenotypic capacities of each cell and its interaction with its ne…
Maximum entropy and population heterogeneity in continuous cell cultures
Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet
Continuous cultures of mammalian cells are complex systems displaying hallmark phenomena of nonlinear dynamics, such as multi-stability, hysteresis, as well as sharp transitions be…
Cell population heterogeneity driven by stochastic partition and growth optimality
Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet, Alexei Vazquez
A fundamental question in biology is how cell populations evolve into different subtypes based on homogeneous processes at the single cell level. Here we show that population bimod…
Missing and spurious interaction in additive, multiplicative and odds ratio models
Jorge Fernandez-de-Cossio, Jorge Fernandez-de-Cossio-Diaz, Toshifumi Takao +1
Additive, multiplicative, and odd ratio neutral models for interactions are for long advocated and controversial in epidemiology. We show here that these commonly advocated models…
Characterizing steady states of genome-scale metabolic networks in continuous cell cultures
Jorge Fernandez-de-Cossio-Diaz, Kalet León, Roberto Mulet
We present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth…
Genetic interactions from first principles
Jorge Fernandez-de-Cossio, Jorge Fernandez-de-Cossio-Diaz, Yasser Perera
We derive a general statistical model of interactions, starting from probabilistic principles and elementary requirements. Prevailing interaction models in biomedical researches di…
Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype
Jorge Fernandez-de-Cossio-Diaz, Andrea De Martino, Roberto Mulet
We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient…
Fast inference of ill-posed problems within a convex space
Jorge Fernandez-de-Cossio-Diaz, Roberto Mulet
In multiple scientific and technological applications we face the problem of having low dimensional data to be justified by a linear model defined in a high dimensional parameter s…
Optimally designed quantum transport across disordered networks
Mattia Walschaers, Jorge Fernandez-de-Cossio Diaz, Roberto Mulet +1
We establish a general mechanism for highly efficient quantum transport through finite, disordered 3D networks. It relies on the interplay of disorder with centro-symmetry and a do…