Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between ...

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 ...

Framework to easily generate complex synthetic data pipelines by visualizing and configuring the pipeline as a computational graph. LangGraph is used as the underlying graph configuration/execution ...

Abstract: The key node identification method based on graph neural network (GNN) is a new network analysis technology, which aims to identify the key nodes in complex networks by deep learning means.

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 ...