arXiv Machine Learning
Structure alone supports efficient visual computation in the Drosophila visual system
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FLYNN: Robust Neural Network for Robot Navigation using Fly Brain Topology
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A Drosophila Whole-Connectome Network Can Learn Human-Designed Cognitive Tasks
Can a biological wiring diagram serve as a useful computational substrate beyond the behaviors for which it evolved? We use the publicly released MaleCNS v1.0 connectome, reconstructed from a single a...
arXiv Machine Learning
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A Drosophila Whole-Connectome Network Can Learn Human-Designed Cognitive Tasks
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arXiv Machine Learning
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Same Compression Principle, Different Geometry: Rate-Distortion Signatures Dissociate Biological and Artificial Visual Systems
arXiv:2603. 01568v2 Announce Type: replace Abstract: Efficient coding theory predicts that biological perceptual systems compress sensory input optimally under resource constraints, with the systematic structure of errors reflecting the geometry of that compression.