121 citations · 140 across the 12 of their papers we have counts for
13 papers
Generative AI and the transformation of Work in Latin America -- Brazil
Carmen Bonfacio, Fernando Schapachnik, Fabio Porto
This survey explores the impact perceived by employers and employees of GenAI in their work activities in Brazil. Generative AI (GenAI) is gradually transforming Brazil workforce,…
Hyperspherical embedding for novel class classification
Rafael S. Pereira, Alexis Joly, Patrick Valduriez +1
Deep learning models have become increasingly useful in many different industries. On the domain of image classification, convolutional neural networks proved the ability to learn…
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…
A note on the complexity of the causal ordering problem
Bernardo Gonçalves, Fabio Porto
In this note we provide a concise report on the complexity of the causal ordering problem, originally introduced by Simon to reason about causal dependencies implicit in systems of…
-DB: A system for data-driven hypothesis management and analytics
Bernardo Gonçalves, Frederico C. Silva, Fabio Porto
The vision of -DB introduces deterministic scientific hypotheses as a kind of uncertain and probabilistic data, and opens some key technical challenges for enabling data-driven…
Design-theoretic encoding of deterministic hypotheses as constraints and correlations into U-relational databases
Bernardo Gonçalves, Fabio Porto
In view of the paradigm shift that makes science ever more data-driven, in this paper we consider deterministic scientific hypotheses as uncertain data. In the form of mathematical…
-DB: Managing scientific hypotheses as uncertain data
Bernardo Gonçalves, Fabio Porto
In view of the paradigm shift that makes science ever more data-driven, we consider deterministic scientific hypotheses as uncertain data. This vision comprises a probabilistic dat…
Managing large-scale scientific hypotheses as uncertain and probabilistic data with support for predictive analytics
Bernardo Gonçalves, Fabio Porto
The sheer scale of high-resolution raw data generated by simulation has motivated non-conventional approaches for data exploration referred as `immersive' and `in situ' query proce…