A deep learning approach to estimate ocean salinity with data sampled with expendable bathythermographs

Author:

Campos Edmo J.D.ORCID,Rocha Cesar B.,Goes MarlosORCID,Dong Shenfu,Lopez HosmayORCID,Goni Gustavo J.

Funder

CNPq

CIMAS

FAPESP

Publisher

Elsevier BV

Reference29 articles.

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3. Berlinghieri, R., Trippe, B.L., Burt, D.R., Giordano, R., Srnivasan, K., Ozgokmen, T., Xia, J., Broderick, T., 2023. Gaussian Processes at the Helm(holtz): A More Fluid Model for Ocean Currents. In: Proceedings of the 40th International Conference on Machine Learning. Honolulu, Hawaii, http://dx.doi.org/10.48550/arXiv.2302.10364, arXiv:2302.10364 [stat.ME].

4. Applications of deep learning to ocean data inference and subgrid parameterization jour;Bolton;Adv. Model. Earth Syst.,2019

5. World ocean database 2018. a.v. mishonov;Boyer,2018

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