Said Ouala

Orcid: 0000-0003-0554-3971

According to our database1, Said Ouala authored at least 20 papers between 2017 and 2023.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework.
Mach. Learn. Sci. Technol., June, 2023

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review.
IEEE CAA J. Autom. Sinica, June, 2023

Online Calibration of Deep Learning Sub-Models for Hybrid Numerical Modeling Systems.
CoRR, 2023

2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning.
CoRR, 2022

2021
Data-driven and learning-based approaches for the modeling, forecasting and reconstruction of geophysical dynamics : application to sea surface dynamics. (Approches basées données et apprentissage pour la modélisation, la prévision et la reconstruction de dynamiques géophysiques : application à la dynamique océanique de surface).
PhD thesis, 2021

Learning Runge-Kutta Integration Schemes for ODE Simulation and Identification.
CoRR, 2021

End-to-End Kalman Filter for the Reconstruction of Sea Surface Dynamics from Satellite Data.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations.
CoRR, 2020

Physically Informed Neural Networks for the Simulation and Data-Assimilation of Geophysical Dynamics.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

Assimilation-Based Learning of Chaotic Dynamical Systems from Noisy and Partial Data.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Learning Latent Dynamics for Partially-Observed Chaotic Systems.
CoRR, 2019

EM-like Learning Chaotic Dynamics from Noisy and Partial Observations.
CoRR, 2019

Learning Ocean Dynamical Priors from Noisy Data Using Assimilation-Derived Neural Nets.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Sea Surface Dynamics Reconstruction Using Neural Networks Based Kalman Filter.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Residual Integration Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2019

Learning Stochastic Representations of Geophysical Dynamics.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature.
Remote. Sens., 2018

Sea Surface Temperature Prediction and Reconstruction Using Patch-Level Neural Network Representations.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Bilinear Residual Neural Network for the Identification and Forecasting of Geophysical Dynamics.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Bilinear residual Neural Network for the identification and forecasting of dynamical systems.
CoRR, 2017


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