Low-Rank Kolmogorov-Arnold Generator Flows for Interpretable Operator Learning

Name: Low-Rank Kolmogorov-Arnold Generator Flows for Interpretable Operator Learning
Uploaded: 2026-10-19T03:53:22.315157+00:00
Duration: 243 s
Description: Kolmogorov–Arnold flow (KAFlow) learns a physical operator's generator using a low-rank symbol space. It achieves exact integration and automatic distillation, significantly reducing errors in dynamics. The method leverages the inherent low-rank structure of position-dependent operators to create an interpretable network that outperforms existing models.

Kolmogorov–Arnold flow (KAFlow) learns a physical operator's generator using a low-rank symbol space. It achieves exact integration and automatic distillation, significantly reducing errors in dynamics. The method leverages the inherent low-rank structure of position-dependent operators to create an interpretable network that outperforms existing models.

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