Federica Bragone

Orcid: 0000-0003-4132-3175

According to our database1, Federica Bragone authored at least 10 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2025
$PINN - a Domain Decomposition Method for Bayesian Physics-Informed Neural Networks.
CoRR, April, 2025

Discovering Partially Known Ordinary Differential Equations: a Case Study on the Chemical Kinetics of Cellulose Degradation.
CoRR, April, 2025

Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks.
CoRR, February, 2025

Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation.
CoRR, January, 2025

MILP initialization for solving parabolic PDEs with PINNs.
CoRR, January, 2025

Automatic learning analysis of flow-induced birefringence in cellulose nanofibrils.
J. Comput. Sci., 2025

2024
Time Series Predictions Based on PCA and LSTM Networks: A Framework for Predicting Brownian Rotary Diffusion of Cellulose Nanofibrils.
Proceedings of the Computational Science - ICCS 2024, 2024

2022
Self-Supervised Transformer Networks for Error Classification of Tightening Traces.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Physics-Informed Neural Networks for prediction of transformer's temperature distribution.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Physics-Informed Neural Networks for Modeling Cellulose Degradation in Power Transformers.
Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022


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