Author

Valentin Duruisseaux

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#artificial intelligence Preprint Oct 2026

Learnable Splines for Unstructured Neural Operators

Neural operators approximate solution operators of partial differential equations at a fraction of the cost of numerical solvers. Efficient grid-based architectures such as the Fourier neural operator (FNO) assume uniform rectangular grids, whereas engineering simulations use large, irregular, and locally refined meshe...

Vignesh Gopakumar, Zhuoyuan Wang, Ander Gray et al. · 0 citations

#machine learning Preprint Sep 2026

Equation Recast for Canonical Operator Learning Across Parametric PDEs

Equation recast is introduced, which reformulates parametric operator learning as the learning of a single canonical operator, and provides a route toward reusable neural PDE solvers combining equation-guided transfer, data efficiency, and monitorable inference.

Qi-Yun Cheng, Valentin Duruisseaux, C. Clauser et al. · 0 citations