ChapBoltzmann Machines Learning Using High Order Decimation. - Enric Farguell; Ferran Mazzanti; Eduardo Gómez-Ramírez (Hybrid Intelligent Systems, 2007)

Boltzmann Machines Reduction by High-Order Decimation. - Enric Farguell; Ferran Mazzanti; Eduardo Gómez-Ramírez (IEEE Trans. Neural Networks, 2008)

Stopping Criteria in Contrastive Divergence: Alternatives to the Reconstruction Error. - David Buchaca Prats; Enrique Romero; Ferran Mazzanti; Jordi Delgado (ICLR (Workshop Poster), 2014)

Weighted contrastive divergence. - Enrique Romero; Ferran Mazzanti; Jordi Delgado; David Buchaca Prats (Neural Networks, 2019)

Efficient Evaluation of the Partition Function of RBMs with Annealed Importance Sampling. - Ferran Mazzanti; Enrique Romero (CoRR, 2020)

Mean field initialization of the Annealed Importance Sampling algorithm for an efficient evaluation of the Partition Function of Restricted Boltzmann Machines. - Arnau Prat Pou; Enrique Romero; Jordi Martí; Ferran Mazzanti (CoRR, 2024)

Learning restricted Boltzmann machines with pattern induced weights. - Jon Garí; Enrique Romero; Ferran Mazzanti (Neurocomputing, 2024)

Machine Learning Prediction of Cardiovascular Risk in Type 1 Diabetes Mellitus Using Radiomics Features from Multimodal Retinal Images. - Ariadna Tohà-Dalmau; Josep Rosinés-Fonoll; Enrique Romero; Ferran Mazzanti; Ruben Martin-Pinardel; Sonia Marias-Perez; Carolina Bernal-Morales; Rafael Castro-Dominguez; Andrea Mendez; Emilio Ortega; Irene Vinagre; Marga Giménez; et al. (CoRR, 2025)