Daniel Civitarese

According to our database, Daniel Civitarese authored at least 15 papers between 2019 and 2023.

Collaborative distances:

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

2023

AI Foundation Models for Weather and Climate: Applications, Design, and Implementation.

S. Karthik Mukkavilli, Daniel Salles Civitarese, Johannes Schmude, Johannes Jakubik, Anne Jones, Nam Nguyen, Christopher Phillips, Sujit Roy, Shraddha Singh, Campbell D. Watson, Raghu K. Ganti, Hendrik F. Hamann, Udaysankar Nair, Rahul Ramachandran, Kommy Weldemariam

CoRR, 2023

TensorBank: Tensor Lakehouse for Foundation Model Training.

Romeo Kienzler, Johannes Schmude, Naomi Simumba, Benedikt Blumenstiel, Marcus Freitag, Daiki Kimura, Zoltan Arnold Nagy, Michael Behrendt, Hendrik F. Hamann, S. Karthik Mukkavilli, Daniel Salles Civitarese

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Workflow provenance in the lifecycle of scientific machine learning.

Renan Souza, Leonardo Guerreiro Azevedo, Vítor Lourenço, Elton F. S. Soares, Raphael Thiago, Rafael Brandão, Daniel Civitarese, Emilio Vital Brazil, Márcio Ferreira Moreno, Patrick Valduriez, Marta Mattoso, Renato Cerqueira, Marco A. S. Netto

Concurr. Comput. Pract. Exp., 2022

Quantum-inspired evolutionary algorithm applied to neural architecture search.

Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco

Appl. Soft Comput., 2022

2021

Enabling Robust Horizon Picking From Small Training Sets.

Andréa Britto Mattos, Daniel Civitarese, Daniela Szwarcman, Matheus Oliveira, Semen Zaytsev, Daniil Semin, Dário A. B. Oliveira

IEEE Trans. Geosci. Remote. Sens., 2021

Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network.

Daniel Salles Civitarese, Daniela Szwarcman, Bianca Zadrozny, Campbell D. Watson

CoRR, 2021

A modular framework for extreme weather generation.

Bianca Zadrozny, Campbell D. Watson, Daniela Szwarcman, Daniel Civitarese, Dário A. B. Oliveira, Eduardo Rodrigues, Jorge Guevara Diaz

CoRR, 2021

2020

Managing Machine Learning Workflow Components.

Márcio Ferreira Moreno, Vítor Lourenço, Sandro Rama Fiorini, Polyana B. da Costa, Rafael Brandão, Daniel Civitarese, Renato Cerqueira

Int. J. Semantic Comput., 2020

2019

Semantic Segmentation of Seismic Images.

Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny

CoRR, 2019

Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation.

Reinaldo Mozart Da Gama e Silva, Lais Baroni, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil

CoRR, 2019

Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation.

Lais Baroni, Reinaldo Mozart Da Gama e Silva, Rodrigo S. Ferreira, Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil

CoRR, 2019

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

Renan Souza, Patrick Valduriez, Marta Mattoso, Renato Cerqueira, Marco Aurélio Stelmar Netto, Leonardo Azevedo, Vítor Lourenço, Elton F. de Souza Soares, Raphael Thiago, Rafael Brandão, Daniel Civitarese, Emilio Vital Brazil, Márcio Ferreira Moreno

Proceedings of the 2019 IEEE/ACM Workflows in Support of Large-Scale Science, 2019

Effective Integration of Symbolic and Connectionist Approaches through a Hybrid Representation.

Márcio Ferreira Moreno, Daniel Civitarese, Rafael Brandão, Renato Cerqueira

Proceedings of the 2019 International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2019), 2019

Quantum-Inspired Neural Architecture Search.

Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco

Proceedings of the International Joint Conference on Neural Networks, 2019

Q-NAS Revisited: Exploring Evolution Fitness to Improve Efficiency.

Daniela Szwarcman, Daniel Civitarese, Marley M. B. R. Vellasco

Proceedings of the 8th Brazilian Conference on Intelligent Systems, 2019