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Physical neural networks

Nonlinear computation with linear systems

Nonlinearity is crucial for sophisticated tasks in machine learning but is often difficult to engineer outside of electronics. By encoding the inputs in parameters of the system, linear systems can realize efficiently trainable nonlinear computations.

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Correspondence to Peter L. McMahon.

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Competing interests

The author is listed as an inventor on several US provisional patent applications relating to optical computing (63/149,974; 63/178,318; 63/392,042).

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McMahon, P.L. Nonlinear computation with linear systems. Nat. Phys. (2024).

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