A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory.
- DOI
- 10.1371/journal.pone.0344827
- Published
- 2026
- Container
- PloS one
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0344827,
title = {A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory.},
author = {Kouokam E},
year = {2026},
journal = {PloS one},
doi = {10.1371/journal.pone.0344827},
url = {https://doi.org/10.1371/journal.pone.0344827}
}RIS
TY - JOUR TI - A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory. AU - Kouokam E PY - 2026 JO - PloS one DO - 10.1371/journal.pone.0344827 UR - https://doi.org/10.1371/journal.pone.0344827 ER -
APA
E, K. (2026). A Hybrid AI-Mathematical approach for epidemic threshold prediction in metapopulation networks: Integrating physics-guided neural networks with spectral graph theory.. PloS one. https://doi.org/10.1371/journal.pone.0344827
Source records
- pubmed · retrieved 2026-11-10T07:58:11.830Z