Peer-reviewedLicence not statedComputer Physics Communications
PINNIES: An efficient physics-informed neural network framework for integral operator problems
- 1Independent Researcher, Isfahan, Iran
- 2Department of Computer and Data Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
- 3International Business University, Toronto, ON, Canada
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BibTeX
@article{aghaei2026pinnies,
title = {{PINNIES: An efficient physics-informed neural network framework for integral operator problems}},
author = {Alireza Afzal Aghaei and Mahdi Movahedian Moghaddam and Kourosh Parand},
journal = {Computer Physics Communications},
year = {2026},
month = jun,
doi = {10.1016/j.cpc.2026.110255},
url = {http://arxiv.org/abs/2409.01899},
}
RIS
TY - JOUR
TI - PINNIES: An efficient physics-informed neural network framework for integral operator problems
AU - Alireza Afzal Aghaei
AU - Mahdi Movahedian Moghaddam
AU - Kourosh Parand
PY - 2026
DA - 2026/06/06
JO - Computer Physics Communications
DO - 10.1016/j.cpc.2026.110255
UR - http://arxiv.org/abs/2409.01899
SN - 0010-4655
SN - 1879-2944
ER -