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Python package built to ease deep learning on graph
...We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graphobject that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks.
BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).