| Pytorch: An imperative style, high-performance deep learning library A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Advances in neural information processing systems 32, 2019 | 48699 | 2019 |
| Automatic differentiation in pytorch A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 14525 | 2017 |
| fairseq: A fast, extensible toolkit for sequence modeling M Ott arXiv preprint arXiv:1904.01038, 2019 | 3187 | 2019 |
| Automatic differentiation in pytorch.(2017) A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 741 | 2017 |
| Learning physical intuition of block towers by example A Lerer, S Gross, R Fergus International conference on machine learning, 430-438, 2016 | 344 | 2016 |
| A multipath network for object detection S Zagoruyko, A Lerer, TY Lin, PO Pinheiro, S Gross, S Chintala, P Dollár arXiv preprint arXiv:1604.02135, 2016 | 290 | 2016 |
| Deep counterfactual regret minimization N Brown, A Lerer, S Gross, T Sandholm International conference on machine learning, 793-802, 2019 | 268 | 2019 |
| Pytorch: An imperative style, high-performance deep learning library, 2019 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703 10, 1912 | 224 | 1912 |
| Training and investigating residual nets (2016) S Gross, M Wilber http://torch.ch/blog/2016/02/04/resnets.html, 2016 | 205* | 2016 |
| Residual energy-based models for text A Bakhtin, Y Deng, S Gross, M Ott, MA Ranzato, A Szlam Journal of Machine Learning Research 22 (40), 1-41, 2021 | 200* | 2021 |
| Semi-supervised learning with context-conditional generative adversarial networks E Denton, S Gross, R Fergus arXiv preprint arXiv:1611.06430, 2016 | 192 | 2016 |
| PyTorch A Paszke, S Gross, S Chintala, G Chanan Computer software. Vers. 0.3 1, 2016 | 122 | 2016 |
| Hard mixtures of experts for large scale weakly supervised vision S Gross, MA Ranzato, A Szlam Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 109 | 2017 |
| PyTorch: An Imperative Style, High-Performance Deep Learning Library. arXiv e-prints: p A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 2019 | 96 | 2019 |
| & Lerer, A.(2017) A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito Automatic differentiation in pytorch, 2017 | 71 | 2017 |
| Airblue: A system for cross-layer wireless protocol development MC Ng, KE Fleming, M Vutukuru, S Gross, Arvind, H Balakrishnan Proceedings of the 6th ACM/IEEE Symposium on Architectures for Networking …, 2010 | 71 | 2010 |
| Bradbury Google J A Paszke, S Gross, F Massa, A Lerer Chanan G., Killeen T., Lin Z., Gimelshein N., Antiga L., Desmaison A., Xamla …, 2019 | 61 | 2019 |
| Advances in Neural Information Processing Systems 32 ed H A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Wallach et al 8024, 2019 | 55 | 2019 |
| Andreas Kö pf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An … A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... Advances in neural information processing systems 32, 8-14, 2019 | 53 | 2019 |
| PyTorch: An imperative style, high-performance deep learning library.(NeurIPS)(2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... | 20 | 1912 |
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