A Library for Learning Neural Operators
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arXiv
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| Autori principali: | , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
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| _version_ | 1866914292252540928 |
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| author | Kossaifi, Jean Kovachki, Nikola Li, Zongyi Pitt, David Liu-Schiaffini, Miguel George, Robert Joseph Bonev, Boris Azizzadenesheli, Kamyar Berner, Julius Duruisseaux, Valentin Anandkumar, Anima |
| author_facet | Kossaifi, Jean Kovachki, Nikola Li, Zongyi Pitt, David Liu-Schiaffini, Miguel George, Robert Joseph Bonev, Boris Azizzadenesheli, Kamyar Berner, Julius Duruisseaux, Valentin Anandkumar, Anima |
| contents | We present NeuralOperator, an open-source Python library for operator learning. Neural operators generalize neural networks to maps between function spaces instead of finite-dimensional Euclidean spaces. They can be trained and inferenced on input and output functions given at various discretizations, satisfying a discretization convergence properties. Part of the official PyTorch Ecosystem, NeuralOperator provides all the tools for training and deploying neural operator models, as well as developing new ones, in a high-quality, tested, open-source package. It combines cutting-edge models and customizability with a gentle learning curve and simple user interface for newcomers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_10354 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Library for Learning Neural Operators Kossaifi, Jean Kovachki, Nikola Li, Zongyi Pitt, David Liu-Schiaffini, Miguel George, Robert Joseph Bonev, Boris Azizzadenesheli, Kamyar Berner, Julius Duruisseaux, Valentin Anandkumar, Anima Machine Learning Artificial Intelligence We present NeuralOperator, an open-source Python library for operator learning. Neural operators generalize neural networks to maps between function spaces instead of finite-dimensional Euclidean spaces. They can be trained and inferenced on input and output functions given at various discretizations, satisfying a discretization convergence properties. Part of the official PyTorch Ecosystem, NeuralOperator provides all the tools for training and deploying neural operator models, as well as developing new ones, in a high-quality, tested, open-source package. It combines cutting-edge models and customizability with a gentle learning curve and simple user interface for newcomers. |
| title | A Library for Learning Neural Operators |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2412.10354 |