5 citations · 11 across the 6 of their papers we have counts for
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cs.LG2024
Variational Graph Auto-Encoder Based Inductive Learning Method for Semi-Supervised Classification
Hanxuan Yang, Zhaoxin Yu, Qingchao Kong +2
Graph representation learning is a fundamental research issue in various domains of applications, of which the inductive learning problem is particularly challenging as it requires…
cs.LG2023
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning
Hanxuan Yang, Qingchao Kong, Wenji Mao
Graph representation learning is a fundamental research theme and can be generalized to benefit multiple downstream tasks from the node and link levels to the higher graph level. I…
cs.LG2021★ 2 cited
A Deep Latent Space Model for Graph Representation Learning
Hanxuan Yang, Qingchao Kong, Wenji Mao
Graph representation learning is a fundamental problem for modeling relational data and benefits a number of downstream applications. Traditional Bayesian-based graph models and re…