Feb. 9, 2024, 5:42 a.m. | Yuan Tian Wenqi Zhou Hao Dong David S. Kammer Olga Fink

cs.LG updates on arXiv.org arxiv.org

Symbolic regression holds great potential for uncovering underlying mathematical and physical relationships from empirical data. While existing transformer-based models have recently achieved significant success in this domain, they face challenges in terms of generalizability and adaptability. Typically, in cases where the output expressions do not adequately fit experimental data, the models lack efficient mechanisms to adapt or modify the expression. This inflexibility hinders their application in real-world scenarios, particularly in discovering unknown physical or biological relationships. Inspired by how human …

adaptability cases challenges cs.ai cs.lg data decision domain experimental face making regression relationships success terms transformer via

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