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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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1 result for “super-parameterization”
Data-driven super-parameterization using deep learning: Experimentation with multi-scale Lorenz 96 systems and transfer-learningphysics.ao-ph

DD-SP uses ML to improve SP for Lorenz 96 systems, outperforming LR and DD-P.

problem Improving computational efficiency in weather/climate modeling.
method Data-driven super-parameterization using recurrent neural networks.
result DD-SP is more accurate and cheaper than SP, especially with scale separation.
weather modelingclimate modelingsuper-parameterizationdata-drivenLorenz 96
2020-02-25abs ↗pdf ↗