AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes HSO-GAT, a topology-adaptive hyperbolic graph attention network that unifies geometric adaptation and message propagation and establishes the monotonic sensitivity of edge-level HSO to degree imbalance and analyzes the validity and radial scaling properties of node-adaptive hyperbolic mappings.
This work proposes Source-Anchored Guidance via Frequency Equalization for Hierarchical RGB-T Alignment and Fusion (SAGE), a unified framework integrating frequency equalization, hierarchical alignment, and subband fusion.
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