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stat.ML2025
Scalable Machine Learning Algorithms using Path Signatures
Csaba Tóth
The interface between stochastic analysis and machine learning is a rapidly evolving field, with path signatures - iterated integrals that provide faithful, hierarchical representa…
stat.ML2023★ 1 cited
Random Fourier Signature Features
Csaba Toth, Harald Oberhauser, Zoltan Szabo
Tensor algebras give rise to one of the most powerful measures of similarity for sequences of arbitrary length called the signature kernel accompanied with attractive theoretical g…
stat.ML2019★ 17 cited
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
Csaba Toth, Harald Oberhauser
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 sequ…