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[Long version] Accelerating Winograd convolutions using symbolic computation and meta-programming
Winograd Schema Problems
David Gregg - Improving the Accuracy and Speed of Winograd Convolution for Deep Neural Networks
Solving the Winograd challenge (Pt. 3)
Session 7B: Optimizing Winograd-Based Convolution with Tensor Cores
CVPR 2022: Channel Balancing for Accurate Quantization of Winograd Convolutions
Session 6B: Optimizing Massively Parallel Winograd Convolution on ARM Processor
DWM: A Decomposable Winograd Method for Convolution Acceleration
tinyML Summit 2021 tiny Talks: Low-precision Winograd Convolution over Residue Number System
Fast Algorithms for Convolutional Neural Networks
Efficient non-fused Winograd on GPUs
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Last Updated: September 30, 2026
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Winograd Minimal Filtering Algorithm Tittle : Fast Convolution based on Cheng Wang, senior vice president of engineering at Flex Logix, talks with Semiconductor Engineering about the This is my presentation for my paper published in EuroSyS 2020 conference related to the acceleration of Material based on Jurafsky and Martin (2019): web.stanford.edu/~jurafsky/slp3/ Slides: ... David Gregg Professor in Computer Science, Trinity College Dublin scss.tcd.ie/David.Gregg ... Linking the parser to the logic engine and deducing some facts. BotCompany.de. Official presentation of the CVPR 2022 poster paper "Channel Balancing for Accurate Quantization of Neural Acceleration Study Paper: DWM: A Decomposable tinyML Summit 2021 tinyml.org/event/summit-2021 tinyTalks CGI2020_Session MACHINE LEARNING FOR GRAPHICS / Efficient non-fused