Shypd.aiThe largest open index of AI toolsOpenHGNN is an open-source toolkit for Heterogeneous Graph Neural Networks based on DGL and PyTorch. It provides easy-to-use interfaces for running experiments with various SOTA models.
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OpenHGNN is an open-source toolkit designed for Heterogeneous Graph Neural Networks (HGNNs), built upon the Deep Graph Library (DGL) and PyTorch. It aims to facilitate research and development in heterogeneous graph-based machine learning by integrating state-of-the-art HGNN models. The toolkit offers easy-to-use interfaces for conducting experiments and supports various tasks including node classification, link prediction, and recommendation. Key features include extensibility for user-defined tasks, models, and datasets, efficiency through DGL's backend, and tools for hyperparameter optimization and visualization. It also supports mini-batch training and distributed training for large-scale graphs.
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