Learning in the Transverse Subspace: a minimal representation for divergence-free operator learning
Read the original at arxiv.org→arXiv:2609.35884v1 Announce Type: new Abstract: Divergence-free vector fields are fundamental state variables in incompressible flows and many PDE systems. Redundant parameterizations, including Neural Conservation...
Original headline: "Learning in the Transverse Subspace: A Minimal Representation for Divergence-Free Operator Learning"
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- Sep 30, 04:00 UTC arXiv cs.LG lead source Learning in the Transverse Subspace: A Minimal Representation for Divergence-Free Operator Learning