all AI news
Towards true discovery of the differential equations. (arXiv:2308.04901v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
Differential equation discovery, a machine learning subfield, is used to
develop interpretable models, particularly in nature-related applications. By
expertly incorporating the general parametric form of the equation of motion
and appropriate differential terms, algorithms can autonomously uncover
equations from data. This paper explores the prerequisites and tools for
independent equation discovery without expert input, eliminating the need for
equation form assumptions. We focus on addressing the challenge of assessing
the adequacy of discovered equations when the correct equation is unknown, …
algorithms applications arxiv data differential differential equation discovery equation general independent machine machine learning nature paper parametric terms tools true