8 citations · 11 across the 6 of their papers we have counts for
4 papers · 1 filter
Deep Cut-informed Graph Embedding and Clustering
Zhiyuan Ning, Zaitian Wang, Ran Zhang +8
Graph clustering aims to divide the graph into different clusters. The recently emerging deep graph clustering approaches are largely built on graph neural networks (GNN). However,…
Towards Graph Prompt Learning: A Survey and Beyond
Qingqing Long, Yuchen Yan, Peiyan Zhang +12
Large-scale "pre-train and prompt learning" paradigms have demonstrated remarkable adaptability, enabling broad applications across diverse domains such as question answering, imag…
DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning
Yifan Wang, Xiao Luo, Chong Chen +3
Graph classification is a critical task in numerous multimedia applications, where graphs are employed to represent diverse types of multimedia data, including images, videos, and…
Density-Based Clustering with Kernel Diffusion
Chao Zheng, Yingjie Chen, Chong Chen +2
Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC. A naive density corresponding to the indicator function of a unit $…