Pretrained models + simulations for our HESSD submission "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets"
| Authors: | |
|---|---|
| Owners: | Frederik Kratzert |
| Type: | Resource |
| Storage: | The size of this resource is 895.7 MB |
| Created: | Jul 18, 2019 at 12:56 p.m. |
| Last updated: | Nov 12, 2021 at 4:48 p.m. (Metadata update) |
| Published date: | Dec 17, 2019 at 8:30 a.m. |
| DOI: | 10.4211/hs.83ea5312635e44dc824eeb99eda12f06 |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
|---|---|
| Views: | 4883 |
| Downloads: | 14266 |
| +1 Votes: | 2 others +1 this |
| Comments: | No comments (yet) |
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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| 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. (2019). 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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