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.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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