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Débora B. Pina

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Journal Articles

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2022
[j2]
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  - journals/jidm/PinaKBSLOM22
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Débora B. Pina, Liliane N. O. Kunstmann, Felipe Bevilaqua, Isabela Siqueira, Alan De Oliveira Lyra, Daniel de Oliveira, Marta Mattoso:
Capturing Provenance from Deep Learning Applications Using Keras-Prov and Colab: a Practical Approach. J. Inf. Data Manag. 13(5) (2022)
2021
[j1]
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Liliane N. O. Kunstmann, Débora B. Pina, Filipe Silva, Aline Paes, Patrick Valduriez, Daniel de Oliveira, Marta Mattoso:
Online Deep Learning Hyperparameter Tuning based on Provenance Analysis. J. Inf. Data Manag. 12(5) (2021)

Conference and Workshop Papers

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2024
[c8]
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  - conf/deem/PinaCK0M24
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Débora B. Pina, Adriane Chapman, Liliane N. O. Kunstmann, Daniel de Oliveira, Marta Mattoso:
DLProv: A Data-Centric Support for Deep Learning Workflow Analyses. DEEM@SIGMOD 2024: 77-85
2023
[c7]
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  - conf/cluster/RosendoMCSPVA23
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Daniel Rosendo, Marta Mattoso, Alexandru Costan, Renan Souza, Débora B. Pina, Patrick Valduriez, Gabriel Antoniu:
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum. CLUSTER 2023: 221-233
[c6]
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  - conf/sbac-pad/OliveiraKPOM23
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Lyncoln S. de Oliveira, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Marta Mattoso:
PINNProv: Provenance for Physics-Informed Neural Networks. SBAC-PADW 2023: 16-23
[c5]
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Débora B. Pina, Adriane Chapman, Daniel de Oliveira, Marta Mattoso:
Deep Learning Provenance Data Integration: a Practical Approach. WWW (Companion Volume) 2023: 1542-1550
2022
[c4]
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Lyncoln S. de Oliveira, Rômulo M. Silva, Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Alvaro L. G. A. Coutinho, Marta Mattoso:
Dados de proveniência para redes neurais guiadas pela Física: o caso da equação eikonal. SBBD 2022: 373-378
2021
[c3]
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Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Provenance Supporting Hyperparameter Analysis in Deep Neural Networks. IPAW 2021: 20-38
2020
[c2]
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Débora B. Pina, Liliane N. O. Kunstmann, Daniel de Oliveira, Patrick Valduriez, Marta Mattoso:
Uma abordagem para coleta e análise de dados de configurações em redes neurais profundas. SBBD 2020: 187-192
2019
[c1]
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  - conf/sbbd/PinaNP0M19
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Débora B. Pina, Liliane Neves, Aline Paes, Daniel de Oliveira, Marta Mattoso:
Análise de Hiperparâmetros em Aplicações de Aprendizado Profundo por meio de Dados de Proveniência. SBBD 2019: 223-228

Informal and Other Publications

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2024
[i2]
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  - journals/corr/abs-2403-15324
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Liliane N. O. Kunstmann, Débora B. Pina, Daniel de Oliveira, Marta Mattoso:
ProvDeploy: Provenance-oriented Containerization of High Performance Computing Scientific Workflows. CoRR abs/2403.15324 (2024)
2023
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  - journals/corr/abs-2307-10658
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Daniel Rosendo, Marta Mattoso, Alexandru Costan, Renan Souza, Débora B. Pina, Patrick Valduriez, Gabriel Antoniu:
ProvLight: Efficient Workflow Provenance Capture on the Edge-to-Cloud Continuum. CoRR abs/2307.10658 (2023)

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