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A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
The main features of benedekrozemberczki/attentionwalk are: Embedding Algorithms, Graph Neural Networks, Geometric Deep Learning: Graph & Irregular Structures.
Projects with overlapping indexed features include: benedekrozemberczki/sine — A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018). benedekrozemberczki/splitter — A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019). benedekrozemberczki/seal-ci — A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019). benedekrozemberczki/sgcn — A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018). benedekrozemberczki/gam — A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018). benedekrozemberczki/graphwaveletneuralnetwork — A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019).