Author

Christoph Brune

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#machine learning Jan 2026

Manifold limit for the training of shallow graph convolutional neural networks

It is proved that $\Gamma-convergence of regularized empirical risk minimization functionals and corresponding convergence of their global minimizers, in the sense of weak convergence of the parameter measures and uniform convergence of the functions over compact sets, provides a formalization of mesh and sample indepe...

Johanna Tengler, Christoph Brune, J. A. Iglesias · arXiv.org · 1 citation

#artificial intelligence Preprint May 2026

When Does Equivariance Help? Canonical Alignment in Neural Fluid Surrogates

The Anchored-Branched Geometric Algebra Transformer (AB-GATr), an E(3)-equivariant surrogate that efficiently predicts coupled surface and volume quantities, is introduced, and results support explicit equivariance for the evaluated hemodynamic tasks with natural orientation variation.

Patryk Rygiel, J. Suk, K. K. Yeung et al. · 0 citations