PINNACLE: PINN Adaptive ColLocation and Experimental points selection

PINNACLE: PINN Adaptive ColLocation and Experimental points selection

11 April 2024

Gregory Kang Ruey Lau

Apivich Hemachandra

See-Kiong Ng

Papers citing "PINNACLE: PINN Adaptive ColLocation and Experimental points selection"

16 / 16 papers shown

Title
Learning and Transferring Physical Models through Derivatives Alessandro Trenta Andrea Cossu Davide Bacciu AI4CE 36 0 0 02 May 2025
Unveiling the Potential of Superexpressive Networks in Implicit Neural Representations Uvini Balasuriya Mudiyanselage Woojin Cho Minju Jo Noseong Park Kookjin Lee 47 0 0 27 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 48 0 0 10 Mar 2025
Parametric Value Approximation for General-sum Differential Games with State Constraints Lei Zhang Mukesh Ghimire Wenlong Zhang Z. Xu Yi Ren 36 0 0 10 Mar 2025
MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning Sofya Dymchenko Abhishek Purandare Bruno Raffin AI4CE 26 0 0 08 Oct 2024
Parameterized Physics-informed Neural Networks for Parameterized PDEs Woojin Cho Minju Jo Haksoo Lim Kookjin Lee Dongeun Lee Sanghyun Hong Noseong Park PINN AI4CE 40 16 1 18 Aug 2024
Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems Amanda A. Howard Bruno Jacob Sarah H. Murphy Alexander Heinlein P. Stinis AI4CE 41 26 0 28 Jun 2024
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions Jingtan Wang Xiaoqiang Lin Rui Qiao Chuan-Sheng Foo Bryan Kian Hsiang Low TDI 37 3 0 07 Jun 2024
Investigating Guiding Information for Adaptive Collocation Point Sampling in PINNs Jose Florido He-Nan Wang Amirul Khan P. Jimack 31 2 0 18 Apr 2024
Feature Mapping in Physics-Informed Neural Networks (PINNs) Chengxi Zeng T. Burghardt A. Gambaruto 41 1 0 10 Feb 2024
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure Haoyu Chu Yuto Miyatake Wenjun Cui Shikui Wei Daisuke Furihata PINN 25 2 0 10 Jan 2024
Generic bounds on the approximation error for physics-informed (and) operator learning Tim De Ryck Siddhartha Mishra PINN 59 59 0 23 May 2022
Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search Yao Shu Zhongxiang Dai Zhaoxuan Wu K. H. Low AI4CE 49 26 0 24 Jan 2022
Deep Active Learning by Leveraging Training Dynamics Haonan Wang Wei Huang Ziwei Wu A. Margenot Hanghang Tong Jingrui He AI4CE 27 33 0 16 Oct 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 71 222 0 26 Apr 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 438 0 18 Dec 2020