It adopts the graph contrastive learning framework to extract the API existence feature fromtwo graphs that model relationships between APIs from different perspectives. Similarly, a CNN-based contrastive learning framework is adopted to extract the API transition feature from two setsof multi-hop ...
Lastly, we conduct contrastive learning on local perspectives (text, audio, visual) within the video subgraphs and the knowledge graph subgraphs, as well as global perspectives, to capture fine-grained semantic information about videos and entities. A series of experimental results on SceneMel ...
Specifically, the proposed model is trained in a self-supervised way by designing a masked graph auto-encoder and a temporal contrastive learning that simultaneously learn the structural and evolutional features from the longitudinal brain networks. Furthermore, we propose a temporal multi-task learning...