Threat actors earlier today published more than 600 malicious packages to the Node Package Manager (npm) index as part of a ...

Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...

Abstract: Graph data modeling is nontrivial due to the challenges to ensure model interpretability and handle data uncertainty. While methods derived from deep learning models, such as graph neural ...

Work Experience :0-1 Roles and Responsibilites: 1. Candidate must have good knowledge of Data Structure 2. Good problem-solving skills 3. Develop responsive and performant user-facing features using ...

Job Description Bachelor's, master's in computer science, Engineering, or a related field Must be proficient in Python. Must have experience in AWS, GCP or Azure. Good experience in database like (SQL ...

Abstract: In recent years, reconstructing features and learning node representations by graph autoencoders (GAE) have attracted much attention in deep graph node clustering. However, existing works ...

Is your feature request related to a problem? Please describe. In the current service graph, I find that the representation of relationships when making asynchronous service calls via message ...

When using the gtk4cairo backend, and using a scaled resolution, part of the graph will be cut off. From the bug reports on Graphs, it seems like with 200% scaling, only 1/2 of the screen is used, and ...