Adam Paszke

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 24

Top Topics

Top Venues

Proc. ACM Program. Lang.

Proc. VLDB Endow.

Publications

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
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR (2024)
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
PartIR: Composing SPMD Partitioning Strategies for Machine Learning. CoRR (2024)
Adam Paszke, Ningning Xie
Infix-Extensible Record Types for Tabular Data. TyDe@ICFP (2023)
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. Proc. ACM Program. Lang. 7 (POPL) (2023)
Dougal Maclaurin, Alexey Radul, Adam Paszke
The Foil: Capture-Avoiding Substitution With No Sharp Edges. CoRR (2022)
Dougal Maclaurin, Alexey Radul, Adam Paszke
The Foil: Capture-Avoiding Substitution With No Sharp Edges. IFL (2022)
Alexey Radul, Adam Paszke, Roy Frostig, Matthew J. Johnson, Dougal Maclaurin
You Only Linearize Once: Tangents Transpose to Gradients. CoRR (2022)
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
Getting to the point: index sets and parallelism-preserving autodiff for pointful array programming. Proc. ACM Program. Lang. 5 (POPL) (2021)
Adam Paszke, Matthew J. Johnson, Roy Frostig, Dougal Maclaurin
Parallelism-preserving automatic differentiation for second-order array languages. FHPNC@ICFP (2021)
Adam Paszke, Brennan Saeta
Tensors Fitting Perfectly. CoRR (2021)
Adam Paszke, Daniel D. Johnson, David Duvenaud, Dimitrios Vytiniotis, Alexey Radul, Matthew J. Johnson, Jonathan Ragan-Kelley, Dougal Maclaurin
Getting to the Point. Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming. CoRR (2021)
Roy Frostig, Matthew J. Johnson, Dougal Maclaurin, Adam Paszke, Alexey Radul
Decomposing reverse-mode automatic differentiation. CoRR (2021)
Ningning Xie, Daniel D. Johnson, Dougal Maclaurin, Adam Paszke
Parallel Algebraic Effect Handlers. CoRR (2021)
Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov
Automap: Towards Ergonomic Automated Parallelism for ML Models. CoRR (2021)
Norman A. Rink, Adam Paszke, Dimitrios Vytiniotis, Georg Stefan Schmid
Memory-efficient array redistribution through portable collective communication. CoRR (2021)
Adam Paszke, Michal Pilipczuk
VC density of set systems defnable in tree-like graphs. CoRR (2020)
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, Soumith Chintala
PyTorch Distributed: Experiences on Accelerating Data Parallel Training. Proc. VLDB Endow. 13 (12) (2020)
Adam Paszke, Michal Pilipczuk
VC Density of Set Systems Definable in Tree-Like Graphs. MFCS (2020)
Shen Li, Yanli Zhao, Rohan Varma, Omkar Salpekar, Pieter Noordhuis, Teng Li, Adam Paszke, Jeff Smith, Brian Vaughan, Pritam Damania, Soumith Chintala
PyTorch Distributed: Experiences on Accelerating Data Parallel Training. CoRR (2020)
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
PyTorch: An Imperative Style, High-Performance Deep Learning Library. CoRR (2019)
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
PyTorch: An Imperative Style, High-Performance Deep Learning Library. NeurIPS (2019)
Alfredo Canziani, Eugenio Culurciello, Adam Paszke
Evaluation of neural network architectures for embedded systems. ISCAS (2017)
Alfredo Canziani, Adam Paszke, Eugenio Culurciello
An Analysis of Deep Neural Network Models for Practical Applications. CoRR (2016)
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, Eugenio Culurciello
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. CoRR (2016)