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ZENODO
Software . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Software . 2023
License: CC BY
Data sources: Datacite
ZENODO
Software . 2023
License: CC BY
Data sources: Datacite
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lmcastellanos/Deep-learning-dynamical-latencies-for-the-analysis-and-reduction-of-combustion-chemistry-kinetics: v2.1

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 23 Oct 2023Publisher:Zenodo
Authors: lmcastellanos;
Code repository: https://github.com/lmcastellanos/Deep-learning-dynamical-latencies-for-the-analysis-and-reduction-of-combustion-chemistry-kinetics/tree/v2.1

doi: 10.5281/zenodo.10034263 , 10.5281/zenodo.10034264

lmcastellanos/Deep-learning-dynamical-latencies-for-the-analysis-and-reduction-of-combustion-chemistry-kinetics: v2.1

Abstract

This release refers to a code repository that includes the datasets and models used in the analysis of potential applications of time-lag autoencoders for the analysis of combustion chemistry kinetics. These codes accompany a paper submitted to the journal "Physics of Fluids".

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    popularity
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    influence
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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