Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
Graph-based semi-supervised learning: A comprehensive review
Semi-supervised learning (SSL) has tremendous value in practice due to the utilization of
both labeled and unlabelled data. An essential class of SSL methods, referred to as graph …
both labeled and unlabelled data. An essential class of SSL methods, referred to as graph …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Hierarchical graph learning for protein–protein interaction
Abstract Protein-Protein Interactions (PPIs) are fundamental means of functions and
signalings in biological systems. The massive growth in demand and cost associated with …
signalings in biological systems. The massive growth in demand and cost associated with …
Interest-aware message-passing GCN for recommendation
Graph Convolution Networks (GCNs) manifest great potential in recommendation. This is
attributed to their capability on learning good user and item embeddings by exploiting the …
attributed to their capability on learning good user and item embeddings by exploiting the …
A federated graph neural network framework for privacy-preserving personalization
Graph neural network (GNN) is effective in modeling high-order interactions and has been
widely used in various personalized applications such as recommendation. However …
widely used in various personalized applications such as recommendation. However …
PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells
Single-cell RNA-seq quantifies biological heterogeneity across both discrete cell types and
continuous cell transitions. Partition-based graph abstraction (PAGA) provides an …
continuous cell transitions. Partition-based graph abstraction (PAGA) provides an …
Graph embedding techniques, applications, and performance: A survey
Graphs, such as social networks, word co-occurrence networks, and communication
networks, occur naturally in various real-world applications. Analyzing them yields insight …
networks, occur naturally in various real-world applications. Analyzing them yields insight …