Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models
Published in Nature Communications, 2025
This paper is about physical unclonable in-memory computing, a novel technique for compute-in-memory to achieve robust and effcient edge acceleration.
Recommended citation: Yue, W., Wu, K., Li, Z., Zhou, J., Wang, Z., Zhang, T., ... & Yang, Y. (2025). Physical unclonable in-memory computing for simultaneous protecting private data and deep learning models. Nature Communications, 16(1), 1031.
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