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A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
A comprehensive benchmark on spectral GNNs relating efficiency and effectiveness.
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
SIGMA: An Efficient Heterophilous Graph Neural Network with Fast Global Aggregation
Graph neural networks (GNNs) realize great success in graph learning but suffer from performance loss when meeting heterophily, i.e. …
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Theoretical spectral bounds for GNN propagation and transformation sparsification.
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Advances in Designing Scalable Graph Neural Networks: The Perspective of Graph Data Management
Graph Neural Network (GNN) is a successful marriage of graph data management and deep learning, leading to notable improvements in …
Advances in Designing Scalable Graph Neural Networks: The Perspective of Graph Data Management
GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs
A GPU-oriented subgraph representation learning algorithm on dynamic data.
GENTI: GPU-powered Walk-based Subgraph Extraction for Scalable Representation Learning on Dynamic Graphs
LD²: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
A scalable heterophilous GNN with lightweight minibatch training.
LD²: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings
Machine Learning for Subgraph Extraction: Methods, Applications and Challenges
Subgraphs are obtained by extracting a subset of vertices and a sub- set of edges from the associated original graphs, and many graph …
Machine Learning for Subgraph Extraction: Methods, Applications and Challenges
Example Searcher: A Spatial Query System via Example
Location search in spatial services such as online maps nowadays is usually based on criteria filtering methods. Due to its algorithmic …
Example Searcher: A Spatial Query System via Example
SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization
A feature-oriented GNN that scales to billion-scale extremely large graphs.
SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization