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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.LG2025
Reformulating Neural Operators in Dimensions for Embedding Evolution
Haoze Song, Zhihao Li, Xiaobo Zhang +3
Neural Operators (NOs) are powerful architectures for learning mappings between function spaces. While most advances focus on refining kernel parameterizations over the -dimensi…
cs.LG2024★ 6 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…