Position Paper on Dataset Engineering to Accelerate Science

no code implementations • 9 Mar 2023 • Emilio Vital Brazil, Eduardo Soares, Lucas Villa Real, Leonardo Azevedo, Vinicius Segura, Luiz Zerkowski, Renato Cerqueira

Moreover, the dataset will be used in most cases as a blueprint of an entity that at any moment can be stored as a table.

Position

Modeling the geospatial evolution of COVID-19 using spatio-temporal convolutional sequence-to-sequence neural networks

no code implementations • 6 May 2021 • Mário Cardoso, André Cavalheiro, Alexandre Borges, Ana F. Duarte, Amílcar Soares, Maria João Pereira, Nuno J. Nunes, Leonardo Azevedo, Arlindo L. Oliveira

Europe was hit hard by the COVID-19 pandemic and Portugal was one of the most affected countries, having suffered three waves in the first twelve months.

Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering

no code implementations • 9 Oct 2019 • Renan Souza, Leonardo Azevedo, Vítor Lourenço, Elton Soares, Raphael Thiago, Rafael Brandão, Daniel Civitarese, Emilio Vital Brazil, Marcio Moreno, Patrick Valduriez, Marta Mattoso, Renato Cerqueira, Marco A. S. Netto

To handle this problem, in this paper we contribute with a detailed characterization of provenance data in the ML lifecycle in CSE; a new provenance data representation, called PROV-ML, built on top of W3C PROV and ML Schema; and extensions to a system that tracks provenance from multiple workflows to address the characteristics of ML and CSE, and to allow for provenance queries with a standard vocabulary.

BIG-bench Machine Learning