DREW: Efficient Winograd CNN Inference with Deep Reuse
Research article (Proceedings of the ACM Web Conference 2022, 2022) · cited 15× · AI/ML
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- [2] ↑ DREW: Efficient Winograd CNN Inference with Deep Reuse — instance of (P31): scholarly article. wikidata.org.
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4ort.xyz Knowledge Graph. (2026). DREW: Efficient Winograd CNN Inference with Deep Reuse. Retrieved May 24, 2026, from https://4ort.xyz/entity/drew-efficient-winograd-cnn-inference-with-deep-reuse
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“DREW: Efficient Winograd CNN Inference with Deep Reuse.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/drew-efficient-winograd-cnn-inference-with-deep-reuse.
BibTeX
@misc{4ortxyz_drew-efficient-winograd-cnn-inference-with-deep-reuse_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DREW: Efficient Winograd CNN Inference with Deep Reuse}}, year = {2026}, url = {https://4ort.xyz/entity/drew-efficient-winograd-cnn-inference-with-deep-reuse}, note = {Accessed: 2026-05-24}}
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According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DREW: Efficient Winograd CNN Inference with Deep Reuse — https://4ort.xyz/entity/drew-efficient-winograd-cnn-inference-with-deep-reuse (retrieved 2026-05-24)
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