2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling
Xiaohui Chen, Jiaxing He, Xu Han +1
Diffusion-based generative graph models have been proven effective in generating high-quality small graphs. However, they need to be more scalable for generating large graphs conta…
cs.LG2022★ 1 cited
PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations
Han Gao, Xu Han, Jiaoyang Huang +2
Recently the Transformer structure has shown good performances in graph learning tasks. However, these Transformer models directly work on graph nodes and may have difficulties lea…
cs.LG2022
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning
Linfeng Liu, Xu Han, Dawei Zhou +1
Subgraph similarity search, one of the core problems in graph search, concerns whether a target graph approximately contains a query graph. The problem is recently touched by neura…