Critical node detection investigates the identification of influential nodes whose removal, either accidental or deliberate, significantly diminishes network connectivity and overall performance.

This leads to increased labor costs and produces suboptimal or even incorrect results. In this article, we propose an end-to-end method for fusing learnable node-level and edge-level augmentation in ...

Differential privacy (DP) has seen immense applications in learning on tabular, image, and sequential data where instance-level privacy is concerned. In learning on graphs, contrastingly, works on ...

A PriorityQueue is a list that always keeps its items sorted based on some rule, like smallest to largest. So, when you take an item out, you always get the one with the highest (or lowest) priority.

Understanding the HackerEarth setup helps you use the tools and see your progress better. Practicing coding problems, ...

Graph Neural Networks (GNNs) are a recent family of Neural Network models specifically designed to harness the inherent structure and dependencies present in graph-structured data, revolutionizing the ...