matsciml
Open MatSci ML Toolkit is a framework for prototyping and scaling out deep learning models for materials discovery supporting widely used materials science datasets, and built on top of PyTorch Lightning, the Deep Graph Library, and PyTorch Geometric.
https://github.com/awslabs/dgl-ke
High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.
https://github.com/awslabs/dgl-lifesci
Python package for graph neural networks in chemistry and biology
https://github.com/awslabs/realtime-fraud-detection-with-gnn-on-dgl
An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.
https://github.com/awslabs/amazon-sagemaker-financial-product-recommender-with-graph-ml
Financial Product Recommendation With Graph ML