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20162025
most citedMachine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space

193 citations · 502 across the 17 of their papers we have counts for

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cs.NE2025

Cannistraci-Hebb Training on Ultra-Sparse Spiking Neural Networks

Yuan Hua, Jilin Zhang, Yingtao Zhang +5

Inspired by the brain's spike-based computation, spiking neural networks (SNNs) inherently possess temporal activation sparsity. However, when it comes to the sparse training of SN…