Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost. It it ...

Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

Graph Signal Processing in Python. Contribute to epfl-lts2/pygsp development by creating an account on GitHub.

Data and models can naturally be represented by graphs. Graph representation of data is used in many areas of science and engineering, making graph matching still currently important. Besides ...