With the explosive growth of online information, recommender systems play a key role to
alleviate such information overload. Due to the important application value of recommender …

Recommendation systems have become popular and effective tools to help users discover
their interesting items by modeling the user preference and item property based on implicit …

In recent years, significant progress has been made in text generation. The latest text
generation models are revolutionizing the domain by generating human-like text. It has …

This comprehensive review provides an in-depth analysis of graph theory, various graph
types, and the role of graph visualization in scientific studies. Graphs serve as powerful tools …

Recent works reveal that feature or label smoothing lies at the core of Graph Neural
Networks (GNNs). Concretely, they show feature smoothing combined with simple linear …

Graph neural networks (GNNs) have achieved state-of-the-art performance in various graph-
based tasks. However, as mainstream GNNs are designed based on the neural message …

Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …

This paper focuses on the joint estimation of parameters and topologies of multivariate
graphical autoregressive moving-average (ARMA) processes. Since the graphical structure …

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 …

The creation and propagation of disinformation on social media is a growing concern. The
widespread dissemination of disinformation can have destructive effects on people's …