Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance

3 March 2023

Papers citing "Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance"

6 / 6 papers shown

Title
Physics-informed DeepONet with stiffness-based loss functions for structural response prediction Bilal Ahmed Yuqing Qiu Diab W. Abueidda Waleed El-Sekelly Borja Garcia de Soto Tarek Abdoun M. Mobasher 13 0 0 02 Sep 2024
Error Analysis and Numerical Algorithm for PDE Approximation with Hidden-Layer Concatenated Physics Informed Neural Networks Yianxia Qian Yongchao Zhang Suchuan Dong PINN 29 0 0 10 Jun 2024
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation Antonio Ferrer-Sánchez Carlos Flores-Garrigós C. Hernani-Morales José J. Orquín-Marqués N. N. Hegade Alejandro Gomez Cadavid Iraitz Montalban Enrique Solano Yolanda Vives-Gilabert J. D. Martín-Guerrero 32 2 0 08 Sep 2023
Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems Paul Escapil-Inchauspé G. A. Ruz 24 32 0 13 May 2022
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 39 489 0 09 Feb 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 170 755 0 13 Mar 2020