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Pretrained models + simulations for our HESSD submission "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets"


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Created: Jul 18, 2019 at 12:56 p.m. (UTC)
Last updated: Nov 12, 2021 at 4:48 p.m. (UTC) (Metadata update)
Published date: Dec 17, 2019 at 8:30 a.m. (UTC)
DOI: 10.4211/hs.83ea5312635e44dc824eeb99eda12f06
Citation: See how to cite this resource
Sharing Status: Published
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Abstract

Contains all models trained for our publication "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets", as well as the evaluated model simulations. The set contains 48 runs in total, stemming from 3 different models (trained with 8 repetitions) and two different loss functions.

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Related Resources

This resource is referenced by Kratzert, F., Klotz, D., Shalev, G., Klambauer, G., Hochreiter S., and Nearing, G.: Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets, Hydrol. Earth Syst. Sci., 2019.

How to Cite

Kratzert, F. (2021). Pretrained models + simulations for our HESSD submission "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets", HydroShare, https://doi.org/10.4211/hs.83ea5312635e44dc824eeb99eda12f06

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
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