Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold
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Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold Networks

24 July 2024

M. Papachristou

Theofilos Papadopoulos

Fotios Anagnostopoulos

Georgios Alexandridis

Papers citing "Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold Networks"

12 / 12 papers shown

Title
Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs Sidharth S. Menon Ameya D. Jagtap PINN 40 0 0 06 May 2025
Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks Yihang Gao Michael K. Ng Vincent Y. F. Tan 66 0 0 17 Feb 2025
KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks Taoran Fang Tianhong Gao Chunping Wang Yihao Shang Wei Chow Lei Chen Yang Yang 44 1 0 23 Jan 2025
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks Tianchi Yu Jingwei Qiu Jiang Yang Ivan V. Oseledets 21 2 0 05 Oct 2024
Deep Learning Alternatives of the Kolmogorov Superposition Theorem Leonardo Ferreira Guilhoto P. Perdikaris 38 7 0 02 Oct 2024
On the expressiveness and spectral bias of KANs Yixuan Wang Jonathan W. Siegel Ziming Liu Thomas Y. Hou 30 9 0 02 Oct 2024
iKAN: Global Incremental Learning with KAN for Human Activity Recognition Across Heterogeneous Datasets Mengxi Liu Sizhen Bian Bo Zhou P. Lukowicz HAI CLL 35 19 0 03 Jun 2024
Kolmogorov-Arnold Network for Satellite Image Classification in Remote Sensing Minjong Cheon 31 42 0 02 Jun 2024
Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation SS Sidharth Keerthana AR R. Gokul Anas KP 51 72 0 12 May 2024
Kolmogorov-Arnold Networks are Radial Basis Function Networks Ziyao Li 43 67 0 10 May 2024
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 37 206 0 16 Jul 2021
Efficient training of physics-informed neural networks via importance sampling M. A. Nabian R. J. Gladstone Hadi Meidani DiffM PINN 66 218 0 26 Apr 2021