Chenhong Zhou

2 accepted papers

2026

SAOT: An Enhanced Locality-Aware Spectral Transformer for Solving PDEs

AAAI 2026technical

Neural operators have shown great potential in solving a family of Partial Differential Equations (PDEs) by modeling the mappings between input and output functions. Fourier Neural Operator (FNO) implements global convolutions via parameterizing the integral operators in Fourier space. However, it o

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2025

Dual-Balancing for Physics-Informed Neural Networks

Chenhong Zhou, Jie Chen, Zaifeng Yang, Ching Eng Png

IJCAI 2025

Physics-informed neural networks (PINNs) have emerged as a new learning paradigm for solving partial differential equations (PDEs) by enforcing the constraints of physical equations, boundary conditions (BCs), and initial conditions (ICs) into the loss function. Despite their successes, vanilla PINN

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