Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances

Csaba Tóth, Harald Oberhauser

Abstract: We develop a Bayesian approach to learning from sequential data by using Gaussian processes (GPs) with so-called signature kernels as covariance functions. This allows to make sequences of differen...