| 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 | 69086 | 2019 |
| Automatic differentiation in pytorch A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 17491 | 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 | 3672 | 2019 |
| Pytorch: An imperative style, high-performance deep learning library B Steiner, Z DeVito, S Chintala, S Gross, A Paske, F Massa, A Lerer, ... | 749 | 2019 |
| 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 | 549 | 1912 |
| Learning physical intuition of block towers by example A Lerer, S Gross, R Fergus International conference on machine learning, 430-438, 2016 | 394 | 2016 |
| Deep counterfactual regret minimization N Brown, A Lerer, S Gross, T Sandholm International conference on machine learning, 793-802, 2019 | 339 | 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 | 297 | 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 | 269* | 2021 |
| Semi-supervised learning with context-conditional generative adversarial networks E Denton, S Gross, R Fergus arXiv preprint arXiv:1611.06430, 2016 | 221 | 2016 |
| Training and investigating residual nets (2016) S Gross, M Wilber http://torch.ch/blog/2016/02/04/resnets.html, 2016 | 215* | 2016 |
| PyTorch: An Imperative Style, High-Performance Deep Learning Library, Dec A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arXiv:1912.01703, 2019 | 206 | 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 | 148 | 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), 5, 1912 | 65 | 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 | 53 | 1912 |
| Pytorch: An imperative style, high-performance deep learning library, 2019. cite A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... arXiv preprint arxiv:1912.01703, 0 | 40* | |
| Facebook A Paszke, S Gross, S Chintala, G Chanan, E Yang ZD, Research, AI, Lin, Z., Desmaison, A., Antiga, L., Srl, O., & Lerer, A …, 0 | 17 | |
| Zeming Lin A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito Alban Desmaison: Luca Antiga, and Adam Lerer. Automatic differentiation in …, 2017 | 10 | 2017 |
| WiLIS: Architectural modeling of wireless systems KE Fleming, MC Ng, S Gross (IEEE ISPASS) IEEE International Symposium on Performance Analysis of …, 2011 | 9 | 2011 |
Adam PaszkeGoogleVerified email at students.mimuw.edu.pl
