1.2k citations · 2.5k across the 71 of their papers we have counts for
71 papers
Intent-aware Recommendation via Disentangled Graph Contrastive Learning
Yuling Wang, Xiao Wang, Xiangzhou Huang +5
Graph neural network (GNN) based recommender systems have become one of the mainstream trends due to the powerful learning ability from user behavior data. Understanding the user i…
Minimum Topology Attacks for Graph Neural Networks
Mengmei Zhang, Xiao Wang, Chuan Shi +3
With the great popularity of Graph Neural Networks (GNNs), their robustness to adversarial topology attacks has received significant attention. Although many attack methods have be…
Provable Training for Graph Contrastive Learning
Yue Yu, Xiao Wang, Mengmei Zhang +2
Graph Contrastive Learning (GCL) has emerged as a popular training approach for learning node embeddings from augmented graphs without labels. Despite the key principle that maximi…
A stochastic block model for community detection in attributed networks
Xiao Wang, Fang Dai, Wenyan Guo +1
Community detection is an important content in complex network analysis. The existing community detection methods in attributed networks mostly focus on only using network structur…
SSTFormer: Bridging Spiking Neural Network and Memory Support Transformer for Frame-Event based Recognition
Xiao Wang, Yao Rong, Zongzhen Wu +4
Event camera-based pattern recognition is a newly arising research topic in recent years. Current researchers usually transform the event streams into images, graphs, or voxels, an…
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs
Yizhen Zheng, He Zhang, Vincent CS Lee +3
Real-world graphs generally have only one kind of tendency in their connections. These connections are either homophily-prone or heterophily-prone. While graphs with homophily-pron…