Scientific Machine Learning Paper Combines Neural Networks with Maxwell’s Equations

Дата публикации: 25-09-2026 07:12:00

An international research team including Prof. Dr. Markus Lange-Hegermann has had its paper selected as a Spotlight at NeurIPS 2026. The paper introduces FLASH-MAX, a new machine learning architecture that reconstructs electromagnetic fields from sparse measurements while exactly satisfying Maxwell’s equations. In experiments, FLASH-MAX achieves a relative validation error of less than 1% using around 1,000 measurement points in just a few seconds. Prof. Dr. Markus Lange-Hegermann also serves as a Senior Area Chair, coordinating the peer review of around 125 submitted papers.

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