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Updated: Oct 14, 2025

Decoding Natural Behavior from Neuroethological Embedding
Published on: October 3, 2025
Neural networks can learn to utilize correlated auxiliary noise
Aida Ahmadzadegan1,2,3, Petar Simidzija4, Ming Li5
1Perimeter Institute for Theoretical Physics, Waterloo, ON, N2L 2Y5, Canada. ahmadzadegan.aida@gmail.com.
Abstract:
We demonstrate that neural networks that process noisy data can learn to exploit, when available, access to auxiliary noise that is correlated with the noise on the data. In effect, the network learns to use the correlated auxiliary noise as an approximate key to decipher its noisy input data. An example of naturally occurring correlated auxiliary noise is the noise due to decoherence. Our results could, therefore, also be of interest, for example, for machine-learned quantum error correction.
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