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20242026
most citedHarnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries

6 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Physics-Consistent Diffusion for Efficient Fluid Super-Resolution via Multiscale Residual Correction

Zhihao Li, Shengwei Dong, Chuang Yi +5

Existing image SR and generic diffusion models transfer poorly to fluid SR: they are sampling-intensive, ignore physical constraints, and often yield spectral mismatch and spurious…

cs.LG2026

From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators

Zhihao Li, Yu Feng, Zhilu Lai +1

Learning PDE dynamics for fluids increasingly relies on neural operators and Transformer-based models, yet these approaches often lack interpretability and struggle with localized,…

cs.LG2026

Structure-Aware Epistemic Uncertainty Quantification for Neural Operator PDE Surrogates

Haoze Song, Zhihao Li, Mengyi Deng +4

Neural operators (NOs) provide fast, resolution-invariant surrogates for mapping input fields to PDE solution fields, but their predictions can exhibit significant epistemic uncert…

cs.CE2025

Neural Preconditioning Operator for Efficient PDE Solves

Zhihao Li, Di Xiao, Zhilu Lai +1

We introduce the Neural Preconditioning Operator (NPO), a novel approach designed to accelerate Krylov solvers in solving large, sparse linear systems derived from partial differen…

cs.LG20246 cited

Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries

Zhihao Li, Haoze Song, Di Xiao +2

Partial Differential Equations (PDEs) underpin many scientific phenomena, yet traditional computational approaches often struggle with complex, nonlinear systems and irregular geom…

cs.CE2024

Parameter estimation of structural dynamics with neural operators enabled surrogate modeling

Mingyuan Zhou, Haoze Song, Wenjing Ye +2

Parameter estimation in structural dynamics generally involves inferring the values of physical, geometric, or even customized parameters based on first principles or expert knowle…