pyiron_workflow is a framework for constructing workflows as computational graphs from simple python functions. Its objective is to make it as easy as possible to create reliable, reusable, and ...

Abstract: Identifying influential nodes in complex networks is vital for understanding their structure and dynamic behavior. Although methods based on a single characteristic of nodes have been ...

Abstract: For real-world graph data, the node class distribution is inherently imbalanced and long-tailed, which naturally leads to a few-shot learning scenario with limited nodes labeled for newly ...