StPINNs - Deep learning framework for approximation of stochastic differential equations
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912989161979904 |
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| author | Baranek, Marcin Przybyłowicz, Paweł |
| author_facet | Baranek, Marcin Przybyłowicz, Paweł |
| contents | In this paper, we introduce the SPINNs (stochastic physics-informed neural networks) in a systematic manner. This provides a mathematical framework for approximating the solution of stochastic differential equations (SDEs) driven by Levy noise using artificial neural networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_14258 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | StPINNs - Deep learning framework for approximation of stochastic differential equations Baranek, Marcin Przybyłowicz, Paweł Numerical Analysis In this paper, we introduce the SPINNs (stochastic physics-informed neural networks) in a systematic manner. This provides a mathematical framework for approximating the solution of stochastic differential equations (SDEs) driven by Levy noise using artificial neural networks. |
| title | StPINNs - Deep learning framework for approximation of stochastic differential equations |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2512.14258 |