Efficiently training SciML models with derivative-informed training data using order truncated imaginary numbers

Computer Methods in Applied Mechanics and Engineering 2026

View at publisher
Authors: Krishna Prasath Logakannan, Mauricio Aristizábal, Geoffrey Bomarito, Zhitong Xu, Shandian Zhe, Robert M. Kirby, Harry R. Millwater, Jacob D. Hochhalter
DOI: 10.1016/j.cma.2026.118789
Cited by: 0
References: 38

Fields of Study & Subjects

Evolutionary Algorithms and Applications Model Reduction and Neural Networks Neural Networks and Applications

Publication details

Journal / source
Computer Methods in Applied Mechanics and Engineering
Volume
452
Pages
118789–118789
Publication date
7 February 2026
Language
EN