PyTorch: An Imperative Style, High-Performance Deep Learning Library A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ... NeurIPS '19: Proceedings of the 33rd International Conference on Neural …, 2019 | 62940* | 2019 |
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation A Paszke, A Chaurasia, S Kim, E Culurciello arXiv preprint arXiv:1606.02147, 2016 | 2811 | 2016 |
JAX: composable transformations of Python+NumPy programs J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ... http://github.com/google/jax, 2018 | 2806 | 2018 |
An Analysis of Deep Neural Network Models for Practical Applications A Canziani, A Paszke, E Culurciello arXiv preprint arXiv:1605.07678, 2016 | 1696 | 2016 |
Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1493 | 2023 |
PyTorch Distributed: Experiences on Accelerating Data Parallel Training S Li, Y Zhao, R Varma, O Salpekar, P Noordhuis, T Li, A Paszke, J Smith, ... Proceedings of the VLDB Endowment 13 (12), 3005-3018, 2020 | 575 | 2020 |
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 361 | 2024 |
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming A Paszke, D Johnson, D Duvenaud, D Vytiniotis, A Radul, M Johnson, ... Proc. ACM Program. Lang. 5 (ICFP), 2021 | 54 | 2021 |
Evaluation of neural network architectures for embedded systems A Canziani, E Culurciello, A Paszke 2017 IEEE international symposium on Circuits and systems (ISCAS), 1-4, 2017 | 51 | 2017 |
You Only Linearize Once: Tangents Transpose to Gradients A Radul, A Paszke, R Frostig, MJ Johnson, D Maclaurin Proceedings of the ACM on Programming Languages 7 (POPL), 1246-1274, 2023 | 25 | 2023 |
Decomposing reverse-mode automatic differentiation R Frostig, MJ Johnson, D Maclaurin, A Paszke, A Radul LAFI 2021, 2021 | 12 | 2021 |
Automap: Towards Ergonomic Automated Parallelism for ML Models M Schaarschmidt, D Grewe, D Vytiniotis, A Paszke, GS Schmid, T Norman, ... ML for Systems (NeurIPS 2021), 2021 | 11 | 2021 |
Parallelism-preserving automatic differentiation for second-order array languages A Paszke, MJ Johnson, R Frostig, D Maclaurin Proceedings of the 9th ACM SIGPLAN International Workshop on Functional High …, 2021 | 7 | 2021 |
VC Density of Set Systems Definable in Tree-Like Graphs A Paszke, M Pilipczuk 45th International Symposium on Mathematical Foundations of Computer Science …, 2020 | 7 | 2020 |
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models A Botev, S De, SL Smith, A Fernando, GC Muraru, R Haroun, L Berrada, ... arXiv preprint arXiv:2404.07839, 2024 | 4 | 2024 |
Memory-efficient array redistribution through portable collective communication NA Rink, A Paszke, D Vytiniotis, GS Schmid arXiv preprint arXiv:2112.01075, 2021 | 4 | 2021 |
Parallel Algebraic Effect Handlers N Xie, DD Johnson, D Maclaurin, A Paszke PEPM 2022, 2021 | 3 | 2021 |
Infix-Extensible Record Types for Tabular Data A Paszke, N Xie Proceedings of the 8th ACM SIGPLAN International Workshop on Type-Driven …, 2023 | 2 | 2023 |
The Foil: Capture-Avoiding Substitution With No Sharp Edges D Maclaurin, A Radul, A Paszke Proceedings of the 34th Symposium on Implementation and Application of …, 2022 | 2 | 2022 |
Tensors Fitting Perfectly A Paszke, B Saeta arXiv preprint arXiv:2102.13254, 2021 | 2 | 2021 |