BestHub
search
Sign in
Tag

Over‑smoothing

2 views collected around this technical thread.

DataFunSummit
DataFunSummit
Feb 13, 2022 · Artificial Intelligence

GPR‑GNN: Adaptive Universal Generalized PageRank Graph Neural Network for Over‑Smoothing and Generalization

This article reviews the Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN), explaining the logical framework and two fundamental defects of traditional GNNs—lack of universality and over‑smoothing—then presents the GPR‑GNN mechanism, theoretical analysis, extensive experiments, and future research directions.

GPR-GNNGraph Neural NetworksGraph Signal Processing
0 likes · 13 min read
GPR‑GNN: Adaptive Universal Generalized PageRank Graph Neural Network for Over‑Smoothing and Generalization
DataFunTalk
DataFunTalk
Oct 10, 2021 · Artificial Intelligence

Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN): Overview, Challenges, and Experimental Insights

This article presents an in‑depth overview of the Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN), explains the two main limitations of conventional GNNs—lack of generality across homophilic and heterophilic graphs and over‑smoothing—describes the GPR‑GNN architecture with learnable propagation weights, and summarizes synthetic and real‑world experiments that demonstrate its superior generality, resistance to over‑smoothing, interpretability, and potential future extensions.

GNNGeneralizationGeneralized PageRank
0 likes · 18 min read
Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN): Overview, Challenges, and Experimental Insights
DataFunSummit
DataFunSummit
Oct 9, 2021 · Artificial Intelligence

Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN): Solving Generality and Over‑Smoothing in Graph Neural Networks

This article presents the Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN), explains the two main limitations of existing GNNs—lack of generality across homophilic and heterophilic graphs and the over‑smoothing problem—and demonstrates through synthetic and real‑world experiments that GPR‑GNN achieves robust node classification while remaining interpretable and parameter‑efficient.

GPR-GNNGraph Neural NetworksICLR
0 likes · 18 min read
Adaptive Universal Generalized PageRank Graph Neural Network (GPR‑GNN): Solving Generality and Over‑Smoothing in Graph Neural Networks