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Lecture notes on rough paths and applications to machine learning
April 11, 2024, 4:41 a.m. | Thomas Cass, Cristopher Salvi
cs.LG updates on arXiv.org arxiv.org
Abstract: These notes expound the recent use of the signature transform and rough path theory in data science and machine learning. We develop the core theory of the signature from first principles and then survey some recent popular applications of this approach, including signature-based kernel methods and neural rough differential equations. The notes are based on a course given by the two authors at Imperial College London.
abstract applications arxiv core cs.lg data data science kernel lecture machine machine learning math.pr math.st notes path popular science stat.th survey theory type
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