no code implementations • 4 Jul 2018 • Laura Aviñó, Matteo Ruffini, Ricard Gavaldà
Generating datasets that "look like" given real ones is an interesting tasks for healthcare applications of ML and many other fields of science and engineering.
no code implementations • 29 Aug 2017 • Matteo Ruffini, Ricard Gavaldà, Esther Limón
In this paper we present a method for the unsupervised clustering of high-dimensional binary data, with a special focus on electronic healthcare records.
1 code implementation • 11 Dec 2016 • Matteo Ruffini, Marta Casanellas, Ricard Gavaldà
This paper presents an algorithm for the unsupervised learning of latent variable models from unlabeled sets of data.
no code implementations • 18 Oct 2016 • Gilles Blondel, Marta Arias, Ricard Gavaldà
In this paper we propose a causal analog to the purely observational Dynamic Bayesian Networks, which we call Dynamic Causal Networks.