Attributed Network Embedding using an Improved Weisfeiler-Lehman Schema and a Novel Deep Skip-Gram
Attributed Network Embedding (ANE) and the representation of its nodes in a low-
dimensional space is a pivotal step in the analysis of real-world networks. One of the biggest …
dimensional space is a pivotal step in the analysis of real-world networks. One of the biggest …
Self-Supervised Graph Representation Learning via Information Bottleneck
J Gu, Z Zheng, W Zhou, Y Zhang, Z Lu, L Yang - Symmetry, 2022 - mdpi.com
Graph representation learning has become a mainstream method for processing network
structured data, and most graph representation learning methods rely heavily on labeling …
structured data, and most graph representation learning methods rely heavily on labeling …
Multi-source Information Fusion Based Attributed Heterogeneous Network Embedding
Attributed heterogeneous information network embedding is an emerging research topic in
the field of network embedding. It can not only embed nodes with complex heterogeneous …
the field of network embedding. It can not only embed nodes with complex heterogeneous …