Work

A deep latent space model for interpretable representation learning on directed graphs

Year: 2024

Type: article

Source: Neurocomputing

DOI: 10.1016/j.neucom.2024.127342

Authors: Hanxuan Yang, Qingchao Kong, Wenji Mao

Institutions: Chinese Academy of Sciences, Institute of Automation, University of Chinese Academy of Sciences

Language: English

Topic: Advanced Graph Neural Networks

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China

Awards: G1966413184, G1997021681, G2319848860, 数据驱动多尺度材料设计的聚类分析方法研究, G7688102596

OpenAlex ID: W4391344813

FWCI: 0.295

Cites: 42

Cited by: 3

Related to: 10