1 citations · 1 across the 1 of their papers we have counts for
6 papers
DJEnsemble: On the Selection of a Disjoint Ensemble of Deep Learning Black-Box Spatio-Temporal Models
Yania Molina Souto, Rafael Pereira, Rocío Zorrilla +6
In this paper, we present a cost-based approach for the automatic selection and allocation of a disjoint ensemble of black-box predictors to answer predictive spatio-temporal queri…
STConvS2S: Spatiotemporal Convolutional Sequence to Sequence Network for Weather Forecasting
Rafaela Castro, Yania M. Souto, Eduardo Ogasawara +2
Applying machine learning models to meteorological data brings many opportunities to the Geosciences field, such as predicting future weather conditions more accurately. In recent…
SAVIME: A Multidimensional System for the Analysis and Visualization of Simulation Data
Hermano Lustosa, Fabio Porto
Scientific applications produce a huge amount of data, which imposes serious management and analysis challenges. In particular, limitations in current database management systems p…
Towards In-transit Analysis on Supercomputing Environments
Allan Santos, Hermano Lustosa, Fabio Porto +1
The drive towards exascale computing is opening an enormous opportunity for more realistic and precise simulations of natural phenomena. The process of simulation, however, involve…
Parallel Computation of PDFs on Big Spatial Data Using Spark
Ji Liu, Noel Moreno Lemus, Esther Pacitti +2
We consider big spatial data, which is typically produced in scientific areas such as geological or seismic interpretation. The spatial data can be produced by observation (e.g. us…
Constellation Queries over Big Data
Fabio Porto, Amir Khatibi, João R. Nobre +3
A geometrical pattern is a set of points with all pairwise distances (or, more generally, relative distances) specified. Finding matches to such patterns has applications to spatia…