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Found 6 papers, 4 papers with code
FedHGN: A Federated Framework for Heterogeneous Graph Neural Networks
In federated heterogeneous graph learning, clients may have private graph schemas.
MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural Networks
Heterogeneous graph neural networks (HGNNs) were proposed for representation learning on structural data with multiple types of nodes and edges.
Retrieving and ranking short medical questions with two stages neural matching model
Internet hospital is a rising business thanks to recent advances in mobile web technology and high demand of health care services.
MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding
A large number of real-world graphs or networks are inherently heterogeneous, involving a diversity of node types and relation types.
Ranked #1 on
Node Clustering
on IMDb
CRNN: A Joint Neural Network for Redundancy Detection
We observe that MGU achieves the optimal runtime and comparable performance against GRU and LSTM.
An Improved System for Sentence-level Novelty Detection in Textual Streams
Novelty detection in news events has long been a difficult problem.
