Bridging observation, theory and numerical simulation of the ocean using Machine Learning

Maike Sonnewald, Redouane Lguensat, Daniel C. Jones, Peter D. Dueben, Julien Brajard, Venkatramani Balaji

Open source

DOI: 10.1088/1748-9326/ac0eb0
Published: 2021-04-26T12:11:51Z
Container: Not recorded
Publisher: arXiv
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1088/1748-9326/ac0eb0,
  title = {Bridging observation, theory and numerical simulation of the ocean using Machine Learning},
  author = {Maike Sonnewald and Redouane Lguensat and Daniel C. Jones and Peter D. Dueben and Julien Brajard and Venkatramani Balaji},
  year = {2021},
  doi = {10.1088/1748-9326/ac0eb0},
  url = {https://doi.org/10.1088/1748-9326/ac0eb0}
}

RIS

TY  - JOUR
TI  - Bridging observation, theory and numerical simulation of the ocean using Machine Learning
AU  - Maike Sonnewald
AU  - Redouane Lguensat
AU  - Daniel C. Jones
AU  - Peter D. Dueben
AU  - Julien Brajard
AU  - Venkatramani Balaji
PY  - 2021
DO  - 10.1088/1748-9326/ac0eb0
UR  - https://doi.org/10.1088/1748-9326/ac0eb0
ER  -

APA

Sonnewald, M., Lguensat, R., Jones, D. C., Dueben, P. D., Brajard, J., & Balaji, V. (2021). Bridging observation, theory and numerical simulation of the ocean using Machine Learning. https://doi.org/10.1088/1748-9326/ac0eb0

Source records

arxiv · retrieved 2026-09-25T20:11:58.069Z