Adam Paszke

26 papers A* 1B 1C 1Journal 19Unranked 4
YearRankTypeTitle / Venue / Authors
2025 — conf
PartIR: Composing SPMD Partitioning Strategies for Machine Learning.
ASPLOS (1)
Sami Alabed, Daniel Belov, Bart Chrzaszcz, Juliana Franco, Dominik Grewe, Dougal Maclaurin, James Molloy, Tom Natan, Tamara Norman, Xiaoyue Pan, Adam Paszke, Norman A. Rink, Michael Schaarschmidt, Timur Sitdikov, Agnieszka Swietlik, Dimitrios Vytiniotis, Joel Wee
2024 J jnl
Parallel Algebraic Effect Handlers.
Proc. ACM Program. Lang.
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
2024 J jnl
PartIR: Composing SPMD Partitioning Strategies for Machine Learning.
CoRR
Sami Alabed, Bart Chrzaszcz, Juliana Franco, Dominik Grewe, Dougal Maclaurin, James Molloy, Tom Natan, Tamara Norman, Xiaoyue Pan, Adam Paszke, Norman A. Rink, Michael Schaarschmidt, Timur Sitdikov, Agnieszka Swietlik, Dimitrios Vytiniotis, Joel Wee
2024 J jnl
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.
CoRR
Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz Gustavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas
2023 — conf
Infix-Extensible Record Types for Tabular Data.
TyDe@ICFP
Adam Paszke, Ningning Xie
2023 J jnl
You Only Linearize Once: Tangents Transpose to Gradients.
Proc. ACM Program. Lang.
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
2022 — conf
The Foil: Capture-Avoiding Substitution With No Sharp Edges.
IFL
Dougal Maclaurin, Alexey Radul, Adam Paszke
2022 J jnl
The Foil: Capture-Avoiding Substitution With No Sharp Edges.
CoRR
Dougal Maclaurin, Alexey Radul, Adam Paszke
2022 J jnl
You Only Linearize Once: Tangents Transpose to Gradients.
CoRR
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
2021 J jnl
Automap: Towards Ergonomic Automated Parallelism for ML Models.
CoRR
Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov
2021 J jnl
Decomposing reverse-mode automatic differentiation.
CoRR
Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul
2021 J jnl
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming.
CoRR
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
2021 J jnl
Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming.
Proc. ACM Program. Lang.
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
2021 J jnl
Memory-efficient array redistribution through portable collective communication.
CoRR
Norman A. Rink, Adam Paszke, Dimitrios Vytiniotis, Georg Stefan Schmid
2021 J jnl
Parallel Algebraic Effect Handlers.
CoRR
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
2021 — conf
Parallelism-preserving automatic differentiation for second-order array languages.
FHPNC@ICFP
Adam Paszke, Matthew J. Johnson, Roy Frostig, Dougal Maclaurin
2021 J jnl
Tensors Fitting Perfectly.
CoRR
Adam Paszke, Brennan Saeta
2020 J jnl
PyTorch Distributed: Experiences on Accelerating Data Parallel Training.
CoRR
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, Soumith Chintala
2020 J jnl
PyTorch Distributed: Experiences on Accelerating Data Parallel Training.
Proc. VLDB Endow.
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, Soumith Chintala
2020 B conf
VC Density of Set Systems Definable in Tree-Like Graphs.
MFCS
Adam Paszke, Michal Pilipczuk
2020 J jnl
VC density of set systems defnable in tree-like graphs.
CoRR
Adam Paszke, Michal Pilipczuk
2019 A* conf
PyTorch: An Imperative Style, High-Performance Deep Learning Library.
NeurIPS
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
2019 J jnl
PyTorch: An Imperative Style, High-Performance Deep Learning Library.
CoRR
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Z. Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, Soumith Chintala
2017 C conf
Evaluation of neural network architectures for embedded systems.
ISCAS
Alfredo Canziani, Eugenio Culurciello, Adam Paszke
2016 J jnl
An Analysis of Deep Neural Network Models for Practical Applications.
CoRR
Alfredo Canziani, Adam Paszke, Eugenio Culurciello
2016 J jnl
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
CoRR
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, Eugenio Culurciello