Self-supervised learning with masked autoencoders has recently gained
po...
Graph clustering is a fundamental task in graph analysis, and recent adv...
Graph neural networks (GNNs) have shown prominent performance on attribu...
Graph Neural Networks (GNNs) have emerged as the de facto standard for
r...
Organ transplant is the essential treatment method for some end-stage
di...
Clinical trials are indispensable in developing new treatments, but they...
Feature preprocessing, which transforms raw input features into numerica...
Graph neural networks (GNNs) have received remarkable success in link
pr...
Graph contrastive learning (GCL) has emerged as an effective tool for
le...
We introduce a novel masked graph autoencoder (MGAE) framework to perfor...
Sequential recommendation has become increasingly essential in various o...
Recent methods in sequential recommendation focus on learning an overall...
Graph representation learning has attracted much attention in supporting...
Networks have been widely used as the data structure for abstracting
rea...
Social network analysis is an important problem in data mining. A fundam...