Lecture notes on rough paths and applications to machine learning
Thomas Cass Cristopher Salvi
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.