G-PARC: Graph-Physics Aware Recurrent Convolutional neural networks for spatiotemporal dynamics on unstructured meshes.
- DOI
- 10.1038/s41598-026-59318-9
- Published
- 2026 Jul 2
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-59318-9,
title = {G-PARC: Graph-Physics Aware Recurrent Convolutional neural networks for spatiotemporal dynamics on unstructured meshes.},
author = {Beerman JT and Abele TJ and Taghizadeh M and Davis A and Gray ZJ and Alemazkoor N and Gao X and Udaykumar HS and Baek SS},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-59318-9},
url = {https://doi.org/10.1038/s41598-026-59318-9}
}RIS
TY - JOUR TI - G-PARC: Graph-Physics Aware Recurrent Convolutional neural networks for spatiotemporal dynamics on unstructured meshes. AU - Beerman JT AU - Abele TJ AU - Taghizadeh M AU - Davis A AU - Gray ZJ AU - Alemazkoor N AU - Gao X AU - Udaykumar HS AU - Baek SS PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-59318-9 UR - https://doi.org/10.1038/s41598-026-59318-9 ER -
APA
JT, B., TJ, A., M, T., A, D., ZJ, G., N, A., X, G., HS, U., & SS, B. (2026). G-PARC: Graph-Physics Aware Recurrent Convolutional neural networks for spatiotemporal dynamics on unstructured meshes.. Scientific reports. https://doi.org/10.1038/s41598-026-59318-9
Source records
- pubmed · retrieved 2026-09-25T19:38:19.412Z