Guillermo L. Grinblat

According to our database, Guillermo L. Grinblat authored at least 16 papers between 2008 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2020

Online Object Detection and Localization on Stereo Visual SLAM System.

Taihú Pire, Javier Corti, Guillermo L. Grinblat

J. Intell. Robotic Syst., 2020

2019

Exploiting GAN Internal Capacity for High-Quality Reconstruction of Natural Images.

Marcos Pividori, Guillermo L. Grinblat, Lucas C. Uzal

CoRR, 2019

2018

Seed-per-pod estimation for plant breeding using deep learning.

Lucas C. Uzal, Guillermo L. Grinblat, Rafael Namías, Mónica G. Larese, Stefano Bianchi, E. N. Morandi, Pablo M. Granitto

Comput. Electron. Agric., 2018

2017

Class-Splitting Generative Adversarial Networks.

Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto

CoRR, 2017

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

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

Toward Large-Scale Vulnerability Discovery using Machine Learning.

Gustavo Grieco, Guillermo Luis Grinblat, Lucas C. Uzal, Sanjay Rawat, Josselin Feist, Laurent Mounier

Proceedings of the Sixth ACM on Conference on Data and Application Security and Privacy, 2016

2015

Nonstationary regression with support vector machines.

Guillermo L. Grinblat, Lucas C. Uzal, Pablo F. Verdes, Pablo M. Granitto

Neural Comput. Appl., 2015

2013

Abrupt change detection with One-Class Time-Adaptive Support Vector Machines.

Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto

Expert Syst. Appl., 2013

2012

Quantized state simulation of spiking neural networks.

Guillermo L. Grinblat, Hernán Ahumada, Ernesto Kofman

Simul., 2012

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

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

Unsupervized Data-Driven Partitioning of Multiclass Problems.

Hernán Ahumada, Guillermo L. Grinblat, Pablo M. Granitto

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

2010

SVM Based Feature Selection: Why Are We Using the Dual?

Guillermo L. Grinblat, Javier Izetta, Pablo M. Granitto

Proceedings of the Advances in Artificial Intelligence, 2010

2008

Time-Adaptive Support Vector Machines.

Guillermo L. Grinblat, Pablo M. Granitto, H. Alejandro Ceccatto

Inteligencia Artif., 2008

REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems.

Hernán Ahumada, Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto, H. Alejandro Ceccatto

Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008