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Fundamental limits to learning closed-form mathematical models from data

Mathematics

Fundamental limits to learning closed-form mathematical models from data

O. Fajardo-fontiveros, I. Reichardt, et al.

This research by Oscar Fajardo-Fontiveros, Ignasi Reichardt, Harry R. De Los Ríos, Jordi Duch, Marta Sales-Pardo, and Roger Guimerà uncovers groundbreaking insights into the challenges of learning mathematical models from noisy data. Discover the pivotal phase transition that determines whether models can be learned effectively or not, along with the innovative use of probabilistic model selection.

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