A Physics-Informed neural network (PINN) for parameter identification in analytical ultracentrifugation (AUC) analysis.
- DOI
- 10.1016/j.cam.2026.117604
- Published
- 2026-03-27
- Container
- J Comput Appl Math
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.cam.2026.117604,
title = {A Physics-Informed neural network (PINN) for parameter identification in analytical ultracentrifugation (AUC) analysis.},
author = {Cao W and Martin R and Demeler B.},
year = {2026},
journal = {J Comput Appl Math},
doi = {10.1016/j.cam.2026.117604},
url = {https://doi.org/10.1016/j.cam.2026.117604}
}RIS
TY - JOUR TI - A Physics-Informed neural network (PINN) for parameter identification in analytical ultracentrifugation (AUC) analysis. AU - Cao W AU - Martin R AU - Demeler B. PY - 2026 JO - J Comput Appl Math DO - 10.1016/j.cam.2026.117604 UR - https://doi.org/10.1016/j.cam.2026.117604 ER -
APA
W, C., R, M., & B., D. (2026). A Physics-Informed neural network (PINN) for parameter identification in analytical ultracentrifugation (AUC) analysis.. J Comput Appl Math. https://doi.org/10.1016/j.cam.2026.117604
Source records
- europe-pmc · retrieved 2026-09-25T22:16:35.783Z