A Library for Learning Neural Operators
I tiakina i:
| I whakaputaina i: | arXiv.org (Dec 17, 2024), p. n/a |
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| Kaituhi matua: | |
| Ētahi atu kaituhi: | , , , , , , , , |
| I whakaputaina: |
Cornell University Library, arXiv.org
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| Ngā marau: | |
| Urunga tuihono: | Citation/Abstract Full text outside of ProQuest |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3145272953 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 035 | |a 3145272953 | ||
| 045 | 0 | |b d20241217 | |
| 100 | 1 | |a Kossaifi, Jean | |
| 245 | 1 | |a A Library for Learning Neural Operators | |
| 260 | |b Cornell University Library, arXiv.org |c Dec 17, 2024 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a 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. Built on top of PyTorch, 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. | |
| 653 | |a Learning curves | ||
| 653 | |a Python | ||
| 653 | |a Function space | ||
| 653 | |a Convergence | ||
| 653 | |a Neural networks | ||
| 653 | |a Operators (mathematics) | ||
| 653 | |a Discretization | ||
| 653 | |a Open source software | ||
| 653 | |a Euclidean geometry | ||
| 700 | 1 | |a Kovachki, Nikola | |
| 700 | 1 | |a Li, Zongyi | |
| 700 | 1 | |a Pitt, David | |
| 700 | 1 | |a Liu-Schiaffini, Miguel | |
| 700 | 1 | |a George, Robert Joseph | |
| 700 | 1 | |a Bonev, Boris | |
| 700 | 1 | |a Azizzadenesheli, Kamyar | |
| 700 | 1 | |a Berner, Julius | |
| 700 | 1 | |a Anandkumar, Anima | |
| 773 | 0 | |t arXiv.org |g (Dec 17, 2024), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3145272953/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/2412.10354 |