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Convergent Temperature Representations in Artificial and Biological Neural Networks

Haesemeyer et al. train convolutional neural networks to navigate temperature gradients to reveal shared representations and processing in artificial and biological networks. Constrained by zebrafish behavior, artificial networks critically rely on fish-like units and make testable predictions about the brain.

from journals https://ift.tt/2OvC4XG
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