Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs

18 April 2024

Papers citing "Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs"

8 / 8 papers shown

Title
Evaluation and Verification of Physics-Informed Neural Models of the Grad-Shafranov Equation Fauzan Nazranda Rizqan Matthew Hole Charles Gretton 82 0 0 29 Apr 2025
PINNACLE: PINN Adaptive ColLocation and Experimental points selection Gregory Kang Ruey Lau Apivich Hemachandra See-Kiong Ng K. H. Low 3DPC 110 18 0 11 Apr 2024
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu Min Zhu Qinyan Tan Yadhu Kartha Lu Lu 86 375 0 21 Jul 2022
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks Shashank Subramanian Robert M. Kirby Michael W. Mahoney A. Gholami 93 26 0 08 Jul 2022
Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method Wensheng Li Chao Zhang Chuncheng Wang Hanting Guan Dacheng Tao DiffM PINN 44 12 0 18 May 2022
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 121 233 0 26 Apr 2021
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 80 459 0 07 Sep 2020
DeepXDE: A deep learning library for solving differential equations Lu Lu Xuhui Meng Zhiping Mao George Karniadakis PINN AI4CE 97 1,533 0 10 Jul 2019