Physics-Embedded Networks: Improving Convergence and Precision of Physics-Informed Neural Networks for Real-Time Applications
- DOI
- 10.1109/tcyb.2025.3650460
- Published
- 2026-05
- Container
- IEEE Transactions on Cybernetics
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tcyb.2025.3650460,
title = {Physics-Embedded Networks: Improving Convergence and Precision of Physics-Informed Neural Networks for Real-Time Applications},
author = {Archit Krishna Kamath and Mir Feroskhan},
year = {2026},
journal = {IEEE Transactions on Cybernetics},
doi = {10.1109/tcyb.2025.3650460},
url = {https://doi.org/10.1109/tcyb.2025.3650460}
}RIS
TY - JOUR TI - Physics-Embedded Networks: Improving Convergence and Precision of Physics-Informed Neural Networks for Real-Time Applications AU - Archit Krishna Kamath AU - Mir Feroskhan PY - 2026 JO - IEEE Transactions on Cybernetics DO - 10.1109/tcyb.2025.3650460 UR - https://doi.org/10.1109/tcyb.2025.3650460 ER -
APA
Kamath, A. K., & Feroskhan, M. (2026). Physics-Embedded Networks: Improving Convergence and Precision of Physics-Informed Neural Networks for Real-Time Applications. IEEE Transactions on Cybernetics. https://doi.org/10.1109/tcyb.2025.3650460
Source records
- crossref · retrieved 2026-11-10T12:06:55.727Z