Débora B. Pina

According to our database, Débora B. Pina authored at least 11 papers between 2019 and 2024.

Collaborative distances:

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

2024

ProvDeploy: Provenance-oriented Containerization of High Performance Computing Scientific Workflows.

Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Marta Mattoso

CoRR, 2024

DLProv: A Data-Centric Support for Deep Learning Workflow Analyses.

Débora B. Pina, Adriane Chapman, Liliane N. O. Kunstmann, Daniel de Oliveira, Marta Mattoso

Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning, 2024

2023

Deep Learning Provenance Data Integration: a Practical Approach.

Débora B. Pina, Adriane Chapman, Daniel de Oliveira, Marta Mattoso

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

PINNProv: Provenance for Physics-Informed Neural Networks.

Lyncoln S. de Oliveira, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Marta Mattoso

Proceedings of the International Symposium on Computer Architecture and High Performance Computing Workshops , 2023

ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum.

Daniel Rosendo, Marta Mattoso, Alexandru Costan, Renan Souza, Débora B. Pina, Patrick Valduriez, Gabriel Antoniu

Proceedings of the IEEE International Conference on Cluster Computing, 2023

2022

Capturing Provenance from Deep Learning Applications Using Keras-Prov and Colab: a Practical Approach.

Débora B. Pina, Liliane N. O. Kunstmann, Felipe Bevilaqua, Isabela Siqueira, Alan De Oliveira Lyra, Daniel de Oliveira, Marta Mattoso

J. Inf. Data Manag., December, 2022

Dados de proveniência para redes neurais guiadas pela Física: o caso da equação eikonal.

Lyncoln S. de Oliveira, Rômulo M. Silva, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Alvaro L. G. A. Coutinho, Marta Mattoso

Proceedings of the 37th Brazilian Symposium on Databases, 2022

2021

Online Deep Learning Hyperparameter Tuning based on Provenance Analysis.

Liliane N. O. Kunstmann, Débora B. Pina, Filipe Silva, Aline Paes, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso

J. Inf. Data Manag., 2021

Provenance Supporting Hyperparameter Analysis in Deep Neural Networks.

Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso

Proceedings of the Provenance and Annotation of Data and Processes, 2021

2020

Uma abordagem para coleta e análise de dados de configurações em redes neurais profundas.

Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso

Proceedings of the 35th Brazilian Symposium on Databases, 2020

2019

Análise de Hiperparâmetros em Aplicações de Aprendizado Profundo por meio de Dados de Proveniência.

Débora B. Pina, Liliane Neves, Aline Paes, Daniel de Oliveira, Marta Mattoso

Proceedings of the 34th Brazilian Symposium on Databases, 2019