| cff-version: 1.2.0 | |
| message: If you use this software, please cite it as below. | |
| title: PyTorch | |
| authors: | |
| - family-names: PyTorch Team | |
| url: https://pytorch.org | |
| preferred-citation: | |
| type: conference-paper | |
| title: "PyTorch: An Imperative Style, High-Performance Deep Learning Library" | |
| authors: | |
| - family-names: Paszke | |
| given-names: Adam | |
| - family-names: Gross | |
| given-names: Sam | |
| - family-names: Massa | |
| given-names: Francisco | |
| - family-names: Lerer | |
| given-names: Adam | |
| - family-names: Bradbury | |
| given-names: James | |
| - family-names: Chanan | |
| given-names: Gregory | |
| - family-names: Killeen | |
| given-names: Trevor | |
| - family-names: Lin | |
| given-names: Zeming | |
| - family-names: Gimelshein | |
| given-names: Natalia | |
| - family-names: Antiga | |
| given-names: Luca | |
| - family-names: Desmaison | |
| given-names: Alban | |
| - family-names: Kopf | |
| given-names: Andreas | |
| - family-names: Yang | |
| given-names: Edward | |
| - family-names: DeVito | |
| given-names: Zachary | |
| - family-names: Raison | |
| given-names: Martin | |
| - family-names: Tejani | |
| given-names: Alykhan | |
| - family-names: Chilamkurthy | |
| given-names: Sasank | |
| - family-names: Steiner | |
| given-names: Benoit | |
| - family-names: Fang | |
| given-names: Lu | |
| - family-names: Bai | |
| given-names: Junjie | |
| - family-names: Chintala | |
| given-names: Soumith | |
| collection-title: Advances in Neural Information Processing Systems 32 | |
| collection-type: proceedings | |
| editors: | |
| - family-names: Wallach | |
| given-names: H. | |
| - family-names: Larochelle | |
| given-names: H. | |
| - family-names: Beygelzimer | |
| given-names: A. | |
| - family-names: "d'Alché-Buc" | |
| given-names: F. | |
| - family-names: Fox | |
| given-names: E. | |
| - family-names: Garnett | |
| given-names: R. | |
| start: 8024 | |
| end: 8035 | |
| year: 2019 | |
| publisher: | |
| name: Curran Associates, Inc. | |
| url: http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf |