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Code for Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

Authors: Dang, Haoning; Wang, Fei; Chen, Yifan; Liu, Zhouyu; Liu, Dong; Wu, Hongchun;

Code for Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

Abstract

This release contains the code associated with the published article: Randomized neural networks for integro-differential equations with application to neutron transport Version: v1.0.0 Release type: final code release for the published article Contents Source code for RaNN-NTE Scripts used for model training, and evaluation Configuration files and environment/dependency information Instructions for reproducing the main results reported in the article Notes This release corresponds to the version of the code used in the published article. If using this code, please cite the associated article and the archived Zenodo record.

If you use this code, please cite the corresponding paper.

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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