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🤖 A Python library for learning and evaluating knowledge graph embeddings
The main features of pykeen/pykeen are: Graph Learning, Geometric Deep Learning: Graph & Irregular Structures.
Projects with overlapping indexed features include: benedekrozemberczki/appnp — A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019). benedekrozemberczki/attentionwalk — A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018). benedekrozemberczki/capsgnn — A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019). benedekrozemberczki/clustergcn — A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional… benedekrozemberczki/gam — A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018). astrazeneca/chemicalx — A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022).
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)