arXiv Machine Learning June 11, 2026 By Kohei Tsuchiyama, Andre Roehm, Takatomo Mihana, Ryoichi Horisaki

Time-multiplexed layer reuse for physical neural networks

Read the original on arXiv Machine Learning →

arXiv:2511. 00044v3 Announce Type: replace Abstract: Physical neural networks (PNNs) are promising candidates for next-generation computing, but existing demonstrations remain several orders of magnitude smaller than modern digital neural networks, whose recent advances have been driven by rapid growth in trainable parameters.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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