Abstract 3D point clouds are a crucial type of data collected by LiDAR sensors and widely
used in transportation applications due to its concise descriptions and accurate localization …

Graph-level anomaly detection (GLAD) aims to identify graphs that exhibit notable
dissimilarity compared to the majority in a collection. However, current works primarily focus …

Deep learning-based recommender systems have achieved remarkable success in recent
years. However, these methods usually heavily rely on labeled data (ie, user-item …

Recently, Graph Neural Networks (GNNs) have become a mainstream recommender system
method, where it captures high-order collaborative signals between nodes by performing …

Recently, deep clustering utilizing Graph Neural Networks has shown good performance in
the graph clustering. However, the structure information of graph was underused in existing …

Social recommendation is gaining increasing attention in various online applications,
including e-commerce and online streaming, where social information is leveraged to …

The recommendation algorithm is an important means to alleviate the information explosion
in the era of big data. There has been a great deal of research into the use of knowledge …

Identifying driver genes contributing to the occurrence and development of cancers plays a
critical role in cancer research and treatment. Some recent computational approaches …

Graph augmentation has received great attention in recent years for graph contrastive
learning (GCL) to learn well-generalized node/graph representations. However, mainstream …

At present, rumors are growing wantonly with the convenience and influence of social
media, becoming a problem that may severely impact social stability and development. The …