Abstract: Graph auto-encoder is considered a framework for unsupervised learning on graph-structured data by representing graphs in a low dimensional space. It has been proved very powerful for graph ...

Abstract: Recently graph auto-encoders have received increasingly widespread attention as one of the important models in the field of deep learning. Existing graph auto-encoder models only use graph ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213164, China School of Computer Science, Northwestern Polytechnical University, Xi’an 710129, China ...

The Border Gateway Protocol (BGP) is crucial for the communication routes of the Internet. Anomalies in BGP can pose a threat to the stability of the Internet. These anomalies, caused by a variety of ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Molecular generation is crucial for advancing drug discovery, materials science, and ...

While threats from outsiders are easier to alleviate, effective ways seldom exist to handle threats from insiders. The key to managing insider threats lies in engineering behavioral features ...

Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new biomarkers for prevention, diagnosis and treatment of complex human diseases. In this paper, we proposed a ...

Identifying drug–target interaction (DTI) is the basis for drug development. However, the method of using biochemical experiments to discover drug-target interactions has low coverage and high costs.