Your vault has a graph. But you can only stare at it. Obsidian's graph view is beautiful, but it can't answer questions — "Which notes have the most links?" "How many hops between these two concepts?" ...

Abstract: Graph Neural Networks (GNNs) exploit topological structures—namely, node-to-node connections—to aggregate contextual information, thereby achieving strong performance across diverse domains.

Abstract: Graph neural networks (GNNs) have emerged as a powerful framework for a wide range of node-level graph learning tasks. However, their performance typically depends on random or minimally ...

An interactive route planning project that models a city road network as a graph and finds optimized routes using core Data Structures and Algorithms concepts. The project supports shortest, fastest, ...