Lin, Zeming

PyTorch: An Imperative Style, High-Performance Deep Learning Library

Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al. (2019) · arXiv

Parallel Computing and Optimization TechniquesComputational Physics and Python Applications

Cited by 31,473

Evolutionary-scale prediction of atomic level protein structure with a language model

Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 5,990

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2021) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 3,286

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · Proceedings of the National Academy of Sciences

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 3,280

Simulating 500 million years of evolution with a language model

Hayes, T., Rao, R., Akin, H., Sofroniew, N. J., Oktay, D., Lin, Z., Verkuil, R., Tran, V. Q., Deaton, J., Wiggert, M., et al. (2025) · Science

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 937

Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play

Sukhbaatar, S., Lin, Z., Kostrikov, I., Synnaeve, G., Szlam, A., & Fergus, R. (2017) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 149