Abstract: Graph convolutional neural networks have demonstrated promising solutions for processing non-Euclidean data in tasks such as node classification. While existing graph convolution models aim ...

Currently each input and output in a nodegraph is their own separate node. This can complicate nodegraphs with many inputs or outputs. It would be interesting to instead have a single "input" node ...

Since ~2025-09-17 IST, my n8n Cloud instance has become unstable and my form-triggered workflows have effectively stopped. The Editor frequently shows a red “Connection lost” banner even though my ...

Abstract: Graphs are ubiquitous in the real world, in graphs, nodes represent entities and edges capture their relationships. Recently, graph neural networks (GNNs) [3]–[6] have been proposed to ...