Graphs are ubiquitous for modeling complex systems involving structured data and relationships. Consequently, graph representation learning, which aims to automatically learn low-dimensional ...

Visual representation learning is ubiquitous in various real-world applications, including visual comprehension, video understanding, multi-modal analysis, human-computer interaction, and urban ...

Such data can also be represented as a graph with nodes (such as user, protein) and branches connecting them. To apply the machine learning methods to graphs one needs to learn a representation of the ...

EdTech company Great Learning launched its new logo which represents its core philosophy of ‘guided growth’ for its learners so that they are able to power ahead in their careers. Through this ...

Content provided by Yanqiao Zhu, the first author of the paper Deep Graph Contrastive Representation Learning. This paper presents a novel contrastive framework for unsupervised graph representation ...

The knowledge graph needs to scale as new members register, new jobs are posted, new companies, skills, and titles appear in member profiles and job descriptions, etc.