Deep learning for surrogate modelling of neXtSIM ...
Contribution to the "11th Sea Ice data assimilation workshop in Oslo". This presentation describes the advance in the work from my PhD. ... : This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative that seeks to improve socie...
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| Format: | Text |
| Language: | English |
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Zenodo
2023
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| Online Access: | https://dx.doi.org/10.5281/zenodo.7828175 https://zenodo.org/record/7828175 |
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openpolar |
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ftdatacite:10.5281/zenodo.7828175 2023-06-11T04:16:30+02:00 Deep learning for surrogate modelling of neXtSIM ... Durand, Charlotte Finn, Tobias Farchi, Alban Bocquet, Marc Òlason, Einar 2023 https://dx.doi.org/10.5281/zenodo.7828175 https://zenodo.org/record/7828175 en eng Zenodo https://dx.doi.org/10.5281/zenodo.7828174 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess Deep learning Sea-ice Physics Sea-ice thickness Surrogate modeling article-journal Text Presentation ScholarlyArticle 2023 ftdatacite https://doi.org/10.5281/zenodo.782817510.5281/zenodo.7828174 2023-05-02T10:06:25Z Contribution to the "11th Sea Ice data assimilation workshop in Oslo". This presentation describes the advance in the work from my PhD. ... : This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative that seeks to improve societal outcomes through the development of emerging science and technologies. ... Text Sea ice DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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ftdatacite |
| language |
English |
| topic |
Deep learning Sea-ice Physics Sea-ice thickness Surrogate modeling |
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Deep learning Sea-ice Physics Sea-ice thickness Surrogate modeling Durand, Charlotte Finn, Tobias Farchi, Alban Bocquet, Marc Òlason, Einar Deep learning for surrogate modelling of neXtSIM ... |
| topic_facet |
Deep learning Sea-ice Physics Sea-ice thickness Surrogate modeling |
| description |
Contribution to the "11th Sea Ice data assimilation workshop in Oslo". This presentation describes the advance in the work from my PhD. ... : This work is a contribution to the project SASIP (grant no. 353), funded by Schmidt Futures – a philanthropic initiative that seeks to improve societal outcomes through the development of emerging science and technologies. ... |
| format |
Text |
| author |
Durand, Charlotte Finn, Tobias Farchi, Alban Bocquet, Marc Òlason, Einar |
| author_facet |
Durand, Charlotte Finn, Tobias Farchi, Alban Bocquet, Marc Òlason, Einar |
| author_sort |
Durand, Charlotte |
| title |
Deep learning for surrogate modelling of neXtSIM ... |
| title_short |
Deep learning for surrogate modelling of neXtSIM ... |
| title_full |
Deep learning for surrogate modelling of neXtSIM ... |
| title_fullStr |
Deep learning for surrogate modelling of neXtSIM ... |
| title_full_unstemmed |
Deep learning for surrogate modelling of neXtSIM ... |
| title_sort |
deep learning for surrogate modelling of nextsim ... |
| publisher |
Zenodo |
| publishDate |
2023 |
| url |
https://dx.doi.org/10.5281/zenodo.7828175 https://zenodo.org/record/7828175 |
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Sea ice |
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Sea ice |
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https://dx.doi.org/10.5281/zenodo.7828174 |
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Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess |
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https://doi.org/10.5281/zenodo.782817510.5281/zenodo.7828174 |
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