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Sagan

Paper

Low-power analogue neural networks with trainable nonlinear connections for continuous control

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AI summary

arXiv:2606. 23742v1 Announce Type: new Abstract: Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear device responses to act as scalar weights.