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ORCIDLiliane N. O. Kunstmann
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2020 – today
- 2024
[c5]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- [i1]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
- [c4]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 - 2022
- [j3]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) - [c3]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
- [j2]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) - [c2]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
- [j1]Carlos Henrique dos S. Barbosa, Liliane N. O. Kunstmann, Rômulo M. Silva, Charlan Dellon da Silva Alves, Bruno S. Silva, Djalma M. S. Filho, Marta Mattoso, Fernando Rochinha, Alvaro L. G. A. Coutinho:
A workflow for seismic imaging with quantified uncertainty. Comput. Geosci. 145: 104615 (2020) - [c1]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
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