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Found 2 papers, 1 papers with code
Semi-Supervised Heterogeneous Graph Learning with Multi-level Data Augmentation
Differing from homogeneous graph, DA in heterogeneous graph has greater challenges: heterogeneity of information requires DA strategies to effectively handle heterogeneous relations, which considers the information contribution of different types of neighbors and edges to the target nodes.
A Survey of Deep Causal Models and Their Industrial Applications
The notion of causality assumes a paramount position within the realm of human cognition.
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