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arXiv Machine Learning By Peiyi Zheng, Yanming Kang, Hans De Sterck, Giang Tran

MOSAIC-SR: Transformer-Guided Symbolic Regression for Scientific Equation Recovery

Read the original on arXiv Machine Learning →

MOSAIC‑SR is a new symbolic regression method that combines a pretrained Transformer with search‑based refinement. The Transformer generates multiple initial sketches, which seed searches that jointly recover equation structure and constants using scale‑aware optimization and symbolic repair. On the SRSD‑Feynman dataset and six other benchmarks, MOSAIC‑SR achieves the highest symbolic solution rate and ranks among the top two in predictive accuracy, even when irrelevant dummy variables are present.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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