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Neural Network Optimization Based on Complex Network Theory: A Survey
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Application of complex systems topologies in artificial neural networks optimization: An overview
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Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
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Inferring network topology from complex dynamics
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Introduction
inferredcites →https://doi.org/10.1103/physrevlett.96.238701openalex-snapshot
Complex Network from Pseudoperiodic Time Series: Topology versus Dynamics
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Statistical mechanics of complex networks
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Convolutional Neural Network Based on Complex Networks for Brain Tumor Image Classification With a Modified Activation Function
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Anti-Injury Function of Complex Spiking Neural Networks Under Random Attack and Its Mechanism Analysis
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Topological Graph Convolutional Network Based on Complex Network Characteristics
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Deep Spiking Neural Network with Spike Count based Learning Rule
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From Decoupling to Reconstruction: A Robust Graph Neural Network Against Topology Attacks
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Scale-Free Networks: A Decade and Beyond
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Emergence of Scaling in Random Networks
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