Lecture notes on rough paths and applications to machine learning
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866914747666923520 |
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| author | Cass, Thomas Salvi, Cristopher |
| author_facet | Cass, Thomas Salvi, Cristopher |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_06583 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Lecture notes on rough paths and applications to machine learning Cass, Thomas Salvi, Cristopher Machine Learning Probability Statistics Theory 60L10, 60L20 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. |
| title | Lecture notes on rough paths and applications to machine learning |
| topic | Machine Learning Probability Statistics Theory 60L10, 60L20 |
| url | https://arxiv.org/abs/2404.06583 |