A User's Guide to $\texttt{KSig}$: GPU-Accelerated Computation of the Signature Kernel
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866929674859315200 |
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| author | Tóth, Csaba Cruz, Danilo Jr Dela Oberhauser, Harald |
| author_facet | Tóth, Csaba Cruz, Danilo Jr Dela Oberhauser, Harald |
| contents | The signature kernel is a positive definite kernel for sequential and temporal data that has become increasingly popular in machine learning applications due to powerful theoretical guarantees, strong empirical performance, and recently introduced various scalable variations. In this chapter, we give a short introduction to $\texttt{KSig}$, a $\texttt{Scikit-Learn}$ compatible Python package that implements various GPU-accelerated algorithms for computing signature kernels, and performing downstream learning tasks. We also introduce a new algorithm based on tensor sketches which gives strong performance compared to existing algorithms. The package is available at https://github.com/tgcsaba/ksig. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07145 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A User's Guide to $\texttt{KSig}$: GPU-Accelerated Computation of the Signature Kernel Tóth, Csaba Cruz, Danilo Jr Dela Oberhauser, Harald Machine Learning The signature kernel is a positive definite kernel for sequential and temporal data that has become increasingly popular in machine learning applications due to powerful theoretical guarantees, strong empirical performance, and recently introduced various scalable variations. In this chapter, we give a short introduction to $\texttt{KSig}$, a $\texttt{Scikit-Learn}$ compatible Python package that implements various GPU-accelerated algorithms for computing signature kernels, and performing downstream learning tasks. We also introduce a new algorithm based on tensor sketches which gives strong performance compared to existing algorithms. The package is available at https://github.com/tgcsaba/ksig. |
| title | A User's Guide to $\texttt{KSig}$: GPU-Accelerated Computation of the Signature Kernel |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2501.07145 |