2 papers
cond-mat.dis-nn2021
Global multivariate model learning from hierarchically correlated data
Edwin Rodriguez Horta, Alejandro Lage, Martin Weigt +1
Inverse statistical physics aims at inferring models compatible with a set of empirical averages estimated from a high-dimensional dataset of independently distributed equilibrium…
q-bio.BM2020
Sparse generative modeling via parameter-reduction of Boltzmann machines: application to protein-sequence families
Pierre Barrat-Charlaix, Anna Paola Muntoni, Kai Shimagaki +2
Boltzmann machines (BM) are widely used as generative models. For example, pairwise Potts models (PM), which are instances of the BM class, provide accurate statistical models of f…