38 citations · 91 across the 10 of their papers we have counts for
10 papers
Physics-Guided Regime Unmixing
Paula Pacheco, Pablo Granitto, Juan B. Cabral
The Linear Mixing Model (LMM) dominates spectral unmixing for its simplicity, but fails under multiple scattering; existing nonlinear models compensate by applying a fixed regime u…
The VISTA Variables in the Vía Láctea eXtended (VVVX) ESO public survey: Completion of the observations and legacy
R. K. Saito, M. Hempel, J. Alonso-García +143
The ESO public survey VISTA Variables in the Vía Láctea (VVV) surveyed the inner Galactic bulge and the adjacent southern Galactic disk from . Upon its conclusion, the c…
Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV
J. B. Cabral, M. Lares, S. Gurovich +2
As most of the modern astronomical sky surveys produce data faster than humans can analyze it, Machine Learning (ML) has become a central tool in Astronomy. Modern ML methods can b…
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 +1
The creation of a 3D map of the bulge using RRLyrae (RRL) is one of the main goals of the VVV(X) surveys. The overwhelming number of sources under analysis request the use of autom…
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning
J. B. Cabral, B. Sánchez, F. Ramos +3
Machine learning algorithms are highly useful for the classification of time series data in astronomy in this era of peta-scale public survey data releases. These methods can facil…
Class-Splitting Generative Adversarial Networks
Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto
Generative Adversarial Networks (GANs) produce systematically better quality samples when class label information is provided., i.e. in the conditional GAN setup. This is still obs…