337 citations · 693 across the 22 of their papers we have counts for
8 papers · 1 filter
Cluster-guided Contrastive Class-imbalanced Graph Classification
Wei Ju, Zhengyang Mao, Siyu Yi +6
This paper studies the problem of class-imbalanced graph classification, which aims at effectively classifying the graph categories in scenarios with imbalanced class distributions…
Hypergraph-enhanced Dual Semi-supervised Graph Classification
Wei Ju, Zhengyang Mao, Siyu Yi +6
In this paper, we study semi-supervised graph classification, which aims at accurately predicting the categories of graphs in scenarios with limited labeled graphs and abundant unl…
Towards Graph Contrastive Learning: A Survey and Beyond
Wei Ju, Yifan Wang, Yifang Qin +10
In recent years, deep learning on graphs has achieved remarkable success in various domains. However, the reliance on annotated graph data remains a significant bottleneck due to i…
COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting
Wei Ju, Yusheng Zhao, Yifang Qin +6
This paper investigates traffic forecasting, which attempts to forecast the future state of traffic based on historical situations. This problem has received ever-increasing attent…
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges
Wei Ju, Siyu Yi, Yifan Wang +10
Graph-structured data exhibits universality and widespread applicability across diverse domains, such as social network analysis, biochemistry, financial fraud detection, and netwo…
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling
Wei Ju, Yiyang Gu, Zhengyang Mao +5
Self-supervised graph representation learning has recently shown considerable promise in a range of fields, including bioinformatics and social networks. A large number of graph co…
PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering
Yifang Qin, Wei Ju, Xiao Luo +3
Collaborative Filtering (CF) is a pivotal research area in recommender systems that capitalizes on collaborative similarities between users and items to provide personalized recomm…
Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends
Hourun Li, Yusheng Zhao, Zhengyang Mao +7
Intelligent Transportation System (ITS) is crucial for improving traffic congestion, reducing accidents, optimizing urban planning, and more. However, the complexity of traffic net…