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ZENODO
Software . 2024
License: CC BY NC
Data sources: ZENODO
ZENODO
Software . 2024
License: CC BY NC
Data sources: Datacite
ZENODO
Software . 2024
License: CC BY NC
Data sources: Datacite
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Probing the limit of hydrologic predictability with the Transformer network

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 04 Sep 2024Publisher:Zenodo
Authors: Liu, Jiangtao; Bian, Yuchen; Lawson, Kathryn; Shen, Chaopeng;

doi: 10.5281/zenodo.13664153 , 10.5281/zenodo.13664154

Probing the limit of hydrologic predictability with the Transformer network

Abstract

This repository contains the code for our paper published in the Journal of Hydrology:Probing the limit of hydrologic predictability with the Transformer networkCitation:Liu, J., Bian, Y., Lawson, K., & Shen, C. (2024). Probing the limit of hydrologic predictability with the Transformer network. Journal of Hydrology, 637, 131389.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average