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20242026
most citedKolmogorov Arnold Informed neural network: A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov Arnold Networks

197 citations · 229 across the 11 of their papers we have counts for

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math.NA2026

Deep Energy Method with Large Language Model assistance: an open-source Streamlit-based platform for solving variational PDEs

Yizheng Wang, Cosmin Anitescu, Mohammad Sadegh Eshaghi +3

Physics-informed neural networks (PINNs) in energy form, also known as the deep energy method (DEM), offer advantages over strong-form PINNs such as lower-order derivatives and few…

math.NA2026

Pretrain Finite Element Method: A Pretraining and Warm-start Framework for PDEs via Physics-Informed Neural Operators

Yizheng Wang, Zhongkai Hao, Mohammad Sadegh Eshaghi +4

We propose a Pretrained Finite Element Method (PFEM),a physics driven framework that bridges the efficiency of neural operator learning with the accuracy and robustness of classica…