SHAKE-GNN: Scalable Hierarchical Kirchhoff-Forest Graph Neural Network

arXiv:2509.22100 · cs.LG, stat.ML · Submitted 2025-09-26 · Read on arXiv

cs.LG, stat.ML

Submitted: 2025-09-26

Updated: 2026-08-29

Terminology

• Kirchhoff Forest — 16× in this paper
• GNNs — 15× in this paper · explained in 2 episodes
• Benchmark — 14× in this paper · explained in 2 episodes
• Graph Neural Networks (GNNs) — 6× in this paper · explained in 7 episodes
• Abstraction — 5× in this paper · explained in 1 episode
• Aggregation — 5× in this paper · explained in 1 episode
• In International Conference on Learning Representations — 4× in this paper
• Representation Learning — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Clustering — 3× in this paper · explained in 2 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Graph Convolutional Network — 3× in this paper
• AUC — 2× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Graph Isomorphism Networks — 2× in this paper
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Adaptive Weighting — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Aggregation Function — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• In International Conference on Machine Learning — 1× in this paper
• Latent Space — 1× in this paper · explained in 7 episodes
• Semi-supervised Learning — 1× in this paper · explained in 4 episodes
• Spectral clustering — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

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