Abstract: Knowledge graphs (KGs) possess a vital role in enhancing the semantic comprehension of extensive datasets across many fields. It facilitate activities like recommendation systems, semantic ...

Abstract: Graph neural networks (GNNs) are capable of modeling graph data using various types of nodes and edges, and thus can be widely used in the fields of recommender systems and bioinformatics.

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 ...

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 ...