Author

M. Ballard

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Preprint Oct 2026

KernelPack-JAX: a meshless differentiable GPU framework for node generation and forward and inverse PDE problems

We present KernelPack-JAX, a meshless, differentiable, GPU framework in JAX for solving forward and inverse PDE problems in domains whose boundaries, including internal obstacles, are given only by samples of their smooth pieces. Our node generator is based on a new stacked representation of piecewise-smooth boundaries...

A. Cattaneo, M. Ballard, R. M. Kirby et al. · 0 citations

#machine learning Preprint Aug 2026

The Frame Kernel Method for Multiscale Operator Learning

The new multiscale frame kernel method is significantly more accurate than popular neural operators on challenging problems from the literature, while simultaneously admitting an a posteriori multiscale decomposition upon generalization.

B. Frieden, Ryan Whitehead, M. Ballard et al. · 0 citations