| 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 | 47478 | 2019 |
| Automatic differentiation in pytorch A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 14026 | 2017 |
| Evolutionary-scale prediction of atomic-level protein structure with a language model Z Lin, H Akin, R Rao, B Hie, Z Zhu, W Lu, N Smetanin, R Verkuil, O Kabeli, ... Science 379 (6637), 1123-1130, 2023 | 1947* | 2023 |
| Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences A Rives, J Meier, T Sercu, S Goyal, Z Lin, J Liu, D Guo, M Ott, CL Zitnick, ... Proceedings of the National Academy of Sciences 118 (15), e2016239118, 2021 | 1921 | 2021 |
| Automatic differentiation in pytorch.(2017) A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito, Z Lin, ... | 733 | 2017 |
| Intrinsic motivation and automatic curricula via asymmetric self-play S Sukhbaatar, Z Lin, I Kostrikov, G Synnaeve, A Szlam, R Fergus arXiv preprint arXiv:1703.05407, 2017 | 429 | 2017 |
| Learning inverse folding from millions of predicted structures C Hsu, R Verkuil, J Liu, Z Lin, B Hie, T Sercu, A Lerer, A Rives International conference on machine learning, 8946-8970, 2022 | 306 | 2022 |
| 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 | 215 | 1912 |
| Episodic exploration for deep deterministic policies: An application to starcraft micromanagement tasks N Usunier, G Synnaeve, Z Lin, S Chintala arXiv preprint arXiv:1609.02993, 2016 | 173 | 2016 |
| Torchcraft: a library for machine learning research on real-time strategy games G Synnaeve, N Nardelli, A Auvolat, S Chintala, T Lacroix, Z Lin, F Richoux, ... arXiv preprint arXiv:1611.00625, 2016 | 138 | 2016 |
| Deepcloak: Masking deep neural network models for robustness against adversarial samples J Gao, B Wang, Z Lin, W Xu, Y Qi arXiv preprint arXiv:1702.06763, 2017 | 113 | 2017 |
| Deep motif: Visualizing genomic sequence classifications J Lanchantin, R Singh, Z Lin, Y Qi arXiv preprint arXiv:1605.01133, 2016 | 101 | 2016 |
| 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 | 73 | 2019 |
| & Lerer, A.(2017) A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito Automatic differentiation in pytorch, 2017 | 70 | 2017 |
| 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 | 54 | 2019 |
| MUST-CNN: a multilayer shift-and-stitch deep convolutional architecture for sequence-based protein structure prediction Z Lin, J Lanchantin, Y Qi Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 54 | 2016 |
| 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 | 52 | 2019 |
| Stardata: A starcraft ai research dataset Z Lin, J Gehring, V Khalidov, G Synnaeve Proceedings of the AAAI Conference on Artificial Intelligence and …, 2017 | 50 | 2017 |
| Growing action spaces G Farquhar, L Gustafson, Z Lin, S Whiteson, N Usunier, G Synnaeve International Conference on Machine Learning, 3040-3051, 2020 | 35 | 2020 |
| Value propagation networks N Nardelli, G Synnaeve, Z Lin, P Kohli, PHS Torr, N Usunier arXiv preprint arXiv:1805.11199, 2018 | 35 | 2018 |
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