Long-tail data distributions are prevalent in many real-world networks,
...
Time series data appears in a variety of applications such as smart
tran...
Contrastive learning is an effective unsupervised method in graph
repres...
Bipartite graphs are powerful data structures to model interactions betw...
Contrastive learning is an effective unsupervised method in graph
repres...
Graph representation learning is crucial for many real-world application...
Contrastive Learning (CL) is one of the most popular self-supervised lea...
Extractive text summarization aims at extracting the most representative...
Networks have been widely used to represent the relations between object...
Co-evolving time series appears in a multitude of applications such as
e...
The global pandemic of COVID-19 has infected millions of people since it...
Chest X-Ray (CXR) images are commonly used for clinical screening and
di...
Adversarial training is a useful approach to promote the learning of
tra...
Cross-domain text classification aims at building a classifier for a tar...
Medical imaging is widely used in clinical practice for diagnosis and
tr...