| 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 | 55409 | 2019 |
| Automatic differentiation in pytorch A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 15873 | 2017 |
| fairseq: A fast, extensible toolkit for sequence modeling M Ott, S Edunov, A Baevski, A Fan, S Gross, N Ng, D Grangier, M Auli arXiv preprint arXiv:1904.01038, 2019 | 3341 | 2019 |
| Learning physical intuition of block towers by example A Lerer, S Gross, R Fergus International conference on machine learning, 430-438, 2016 | 365 | 2016 |
| Pytorch: An imperative style, high-performance deep learning library. arXiv 2019 A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703 10, 1912 | 324 | 1912 |
| Deep counterfactual regret minimization N Brown, A Lerer, S Gross, T Sandholm International conference on machine learning, 793-802, 2019 | 294 | 2019 |
| 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 | 286 | 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 | 218* | 2021 |
| Training and investigating residual nets (2016) S Gross, M Wilber http://torch.ch/blog/2016/02/04/resnets.html, 2016 | 207* | 2016 |
| Semi-supervised learning with context-conditional generative adversarial networks E Denton, S Gross, R Fergus arXiv preprint arXiv:1611.06430, 2016 | 203 | 2016 |
| PyTorch: an imperative style A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... High-Performance Deep Learning Library 12, 2019 | 192 | 2019 |
| 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 | 117 | 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 | 77 | 2010 |
| An imperative style, high-performance deep learning library A Paszke, S Gross, F Massa, A Lerer, JP Bradbury, G Chanan, T Killeen, ... Adv. Neural Inf. Process. Syst 32, 8026, 1912 | 41 | 1912 |
| Pytorch: an imperative style, high-performance deep learning library. CoRR abs/1912.01703 (2019) A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 1912 | 41 | 1912 |
| WiLIS: Architectural modeling of wireless systems KE Fleming, MC Ng, S Gross (IEEE ISPASS) IEEE International Symposium on Performance Analysis of …, 2011 | 9 | 2011 |
| Pytorch: An imperative style, high-performance deep learning library, vol. 32 A Paszke, S Gross, F Massa Curran Associates, Inc, 8024-8035, 0 | 2 | |
| G, Chanan, E A Paszke, S Gross, S Chintala Yang, Z. DeVito, Z. Lin, A. Desmaison A, L. Antiga, and A. Lerer,“PyTorch …, 0 | 2 | |
| Hardware implementation of wireless bit rate adaptation SA Gross Massachusetts Institute of Technology, 2010 | | 2010 |
Adam PaszkeGoogleVerifisert e-postadresse på students.mimuw.edu.pl