Selecting Diverse Members of Neural Network Ensembles. - Hugo D. Navone; Pablo F. Verdes; Pablo M. Granitto; H. Alejandro Ceccatto (SBRN, 2000)

A Learning Algorithm For Neural Network Ensembles. - Hugo D. Navone; Pablo M. Granitto; Pablo F. Verdes; H. Alejandro Ceccatto (Inteligencia Artif., 2001)

A Late-Stopping Method for Optimal Aggregation of Neural Networks. - Pablo M. Granitto; Pablo F. Verdes; Hugo D. Navone; H. Alejandro Ceccatto (Int. J. Neural Syst., 2001)

Aggregation Algorithms for Neural Network Ensemble Construction . - Pablo M. Granitto; Pablo F. Verdes; Hugo D. Navone; H. Alejandro Ceccatto (SBRN, 2002)

Extracting Driving Signals from Non-Stationary Time Series. - María I. Széliga; Pablo F. Verdes; Pablo M. Granitto; H. Alejandro Ceccatto (SBRN, 2002)

Artificial Neural Network Learning of Nonstationary Behavior in Time Series. - María I. Széliga; Pablo F. Verdes; Pablo M. Granitto; H. Alejandro Ceccatto (Int. J. Neural Syst., 2003)

Prediction of the CATS benchmark exploiting time-reversal symmetry. - Pablo F. Verdes; Pablo M. Granitto; María I. Széliga; Alejandro Rébola; H. Alejandro Ceccatto (IJCNN, 2004)

Neural network ensembles: evaluation of aggregation algorithms. - Pablo M. Granitto; Pablo F. Verdes; H. Alejandro Ceccatto (Artif. Intell., 2005)

Gene Set Enrichment Analysis Using Non-parametric Scores. - Ariel E. Bayá; Mónica G. Larese; Pablo M. Granitto; Juan Carlos Gomez; Elizabeth Tapia (BSB, 2007)

Symmetric-embedding prediction of the CATS benchmark. - Pablo F. Verdes; Pablo M. Granitto; María I. Széliga; Alejandro Rébola; H. Alejandro Ceccatto (Neurocomputing, 2007)

REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems. - Hernán Ahumada; Guillermo L. Grinblat; Lucas C. Uzal; Pablo M. Granitto; H. Alejandro Ceccatto (HIS, 2008)

Efficient Feature Selection for PTR-MS Fingerprinting of Agroindustrial Products. - Pablo M. Granitto; Franco Biasioli; Cesare Furlanello; Flavia Gasperi (ICANN (2), 2008)

ISOMAP based metrics for clustering. - Ariel E. Bayá; Pablo M. Granitto (Inteligencia Artif., 2008)

Time-Adaptive Support Vector Machines. - Guillermo L. Grinblat; Pablo M. Granitto; H. Alejandro Ceccatto (Inteligencia Artif., 2008)

Feature selection on wide multiclass problems using OVA-RFE. - Pablo M. Granitto; Andrés Burgos (Inteligencia Artif., 2009)

Improved Graph-Based Metrics for Clustering High-Dimensional Datasets. - Ariel E. Bayá; Pablo M. Granitto (IBERAMIA, 2010)

SVM Based Feature Selection: Why Are We Using the Dual? - Guillermo L. Grinblat; Javier Izetta; Pablo M. Granitto (IBERAMIA, 2010)

Learning to Discover Faulty Spots in cDNA Microarrays. - Mónica G. Larese; Pablo M. Granitto; Juan C. Gómez (IBERAMIA, 2010)

Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering - Ariel E. Bayá; Pablo M. Granitto (CoRR, 2010)

Unsupervized Data-Driven Partitioning of Multiclass Problems. - Hernán Ahumada; Guillermo L. Grinblat; Pablo M. Granitto (ICANN (1), 2011)

Improved Gene Expression Clustering with the Parameter-Free PKNNG Metric. - Ariel E. Bayá; Pablo M. Granitto (BSB, 2011)

Clustering gene expression data with a penalized graph-based metric. - Ariel E. Bayá; Pablo M. Granitto (BMC Bioinform., 2011)

Evaluation of a new hybrid algorithm for highly imbalanced classification problems. - Hernán Ahumada; Guillermo L. Grinblat; Lucas C. Uzal; H. Alejandro Ceccatto; Pablo M. Granitto (Int. J. Hybrid Intell. Syst., 2011)

Solving Nonstationary Classification Problems With Coupled Support Vector Machines. - Guillermo L. Grinblat; Lucas C. Uzal; H. Alejandro Ceccatto; Pablo M. Granitto (IEEE Trans. Neural Networks, 2011)

A Simple Hybrid Method for Semi-Supervised Learning. - Hernán Ahumada; Pablo M. Granitto (CIARP, 2012)

Legume Identification by Leaf Vein Images Classification. - Mónica G. Larese; Roque M. Craviotto; Miriam R. Arango; Carina Gallo; Pablo M. Granitto (CIARP, 2012)

Abrupt change detection with One-Class Time-Adaptive Support Vector Machines. - Guillermo L. Grinblat; Lucas C. Uzal; Pablo M. Granitto (Expert Syst. Appl., 2013)

Spot defects detection in cDNA microarray images. - Mónica G. Larese; Pablo M. Granitto; Juan C. Gómez (Pattern Anal. Appl., 2013)

How Many Clusters: A Validation Index for Arbitrary-Shaped Clusters. - Ariel E. Bayá; Pablo M. Granitto (IEEE ACM Trans. Comput. Biol. Bioinform., 2013)

Hybrid Consensus Learning for Legume Species and Cultivars Classification. - Mónica G. Larese; Pablo M. Granitto (ECCV Workshops (4), 2014)

Multiscale recognition of legume varieties based on leaf venation images. - Mónica G. Larese; Ariel E. Bayá; Roque M. Craviotto; Miriam R. Arango; Carina Gallo; Pablo M. Granitto (Expert Syst. Appl., 2014)

Automatic classification of legumes using leaf vein image features. - Mónica G. Larese; Rafael Namías; Roque M. Craviotto; Miriam R. Arango; Carina Gallo; Pablo M. Granitto (Pattern Recognit., 2014)

Nonstationary regression with support vector machines. - Guillermo L. Grinblat; Lucas C. Uzal; Pablo F. Verdes; Pablo M. Granitto (Neural Comput. Appl., 2015)

Deep learning for plant identification using vein morphological patterns. - Guillermo L. Grinblat; Lucas C. Uzal; Mónica G. Larese; Pablo M. Granitto (Comput. Electron. Agric., 2016)

Inferring unknown biological function by integration of GO annotations and gene expression data. - Guillermo L. Grinblat; Ariel E. Bayá; Diego H. Milone; Pablo M. Granitto; Georgina Stegmayer (CoRR, 2016)

Clustering using PK-D: A connectivity and density dissimilarity. - Ariel E. Bayá; Mónica G. Larese; Pablo M. Granitto (Expert Syst. Appl., 2016)

Finding local leaf vein patterns for legume characterization and classification. - Mónica G. Larese; Pablo M. Granitto (Mach. Vis. Appl., 2016)

Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines. - Juan B. Cabral; Bruno Sánchez; Martin Beroiz; Mariano Domínguez; Marcelo Lares; Sebastián Gurovich; Pablo M. Granitto (Astron. Comput., 2017)

Class-Splitting Generative Adversarial Networks. - Guillermo L. Grinblat; Lucas C. Uzal; Pablo M. Granitto (CoRR, 2017)

Improved multiclass feature selection via list combination. - Javier Izetta; Pablo F. Verdes; Pablo M. Granitto (Expert Syst. Appl., 2017)

From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning. - Juan B. Cabral; Bruno Sánchez; Felipe Ramos; Sebastián Gurovich; Pablo M. Granitto; Jacob VanderPlas (Astron. Comput., 2018)

Seed-per-pod estimation for plant breeding using deep learning. - Lucas C. Uzal; Guillermo L. Grinblat; Rafael Namías; Mónica G. Larese; Stefano Bianchi; Eligio N. Morandi; Pablo M. Granitto (Comput. Electron. Agric., 2018)

Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. - Guillermo Leale; Ariel E. Bayá; Diego H. Milone; Pablo M. Granitto; Georgina Stegmayer (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Automatic Catalog of RRLyrae from 14 million VVV Light Curves: How far can we go with traditional machine-learning? - Juan B. Cabral; Felipe Ramos; Sebastián Gurovich; Pablo M. Granitto (CoRR, 2020)

Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV. - Juan B. Cabral; Marcelo Lares; Sebastián Gurovich; D. Minniti; Pablo M. Granitto (CoRR, 2021)