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TOOL
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About

Sparse-SNN is a browser-runnable demo of a sparsely connected spiking neural network (5% connection density) built from leaky-integrate-and-fire neurons, with connectivity masks derived from Drosophila connectome statistics. It classifies hand-drawn MNIST and Fashion-MNIST digits via ONNX Runtime Web, activating only about 8% of neurons per frame and estimating roughly 112x lower energy use than a dense model by replacing multiply-accumulates with simple additions.

Why it made the leaderboard

You can draw a digit and watch a 5%-density spiking network (Drosophila connectome-inspired) classify it in the browser using only additions, with the author's own honest accounting of where the approach underperforms a dense baseline.

Tags

spiking-neural-networkonnxneuroscienceresearch-demo

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