Adam Paszke
Adam Paszke
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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
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
JAX: composable transformations of Python+NumPy programs
J Bradbury, R Frostig, P Hawkins, MJ Johnson, C Leary, D Maclaurin, ..., 2018
An Analysis of Deep Neural Network Models for Practical Applications
A Canziani, A Paszke, E Culurciello
arXiv preprint arXiv:1605.07678, 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
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
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
& Lerer, A.(2017)
A Paszke, S Gross, S Chintala, G Chanan, E Yang, Z DeVito
Automatic differentiation in pytorch, 2017
Advances in Neural Information Processing Systems 32, Curran Associates
A Paszke, S Gross, F Massa, A Lerer, J Bradbury, G Chanan, T Killeen, ...
Inc., New York, 8024, 2019
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
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
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
Decomposing reverse-mode automatic differentiation
R Frostig, MJ Johnson, D Maclaurin, A Paszke, A Radul
LAFI 2021, 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
VC Density of Set Systems Definable in Tree-Like Graphs
A Paszke, M Pilipczuk
45th International Symposium on Mathematical Foundations of Computer Science …, 2020
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
Pytorch: an imperative style, high-performance deep learning library. In eds. Wallach, H. et al
A Paszke
Advances in Neural Information Processing Systems, 8026-8037, 0
Memory-efficient array redistribution through portable collective communication
NA Rink, A Paszke, D Vytiniotis, GS Schmid
arXiv preprint arXiv:2112.01075, 2021
Tensors Fitting Perfectly
A Paszke, B Saeta
arXiv preprint arXiv:2102.13254, 2021
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
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