Trending repositories for topic graph-embedding
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".
Deep and conventional community detection related papers, implementations, datasets, and tools.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
A collection of important graph embedding, classification and representation learning papers with implementations.
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Deep and conventional community detection related papers, implementations, datasets, and tools.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
A collection of important graph embedding, classification and representation learning papers with implementations.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
Deep and conventional community detection related papers, implementations, datasets, and tools.
A repository of pretty cool datasets that I collected for network science and machine learning research.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
The reference implementation of "Multi-scale Attributed Node Embedding". (Journal of Complex Networks 2021)
A collection of important graph embedding, classification and representation learning papers with implementations.
Recommender Systems Paperlist that I am interested in
Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
The integration of HugeGraph with artificial intelligence
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
The reference implementation of "Multi-scale Attributed Node Embedding". (Journal of Complex Networks 2021)
Summary of Spatio-Temporal Representation Learning Models.
Deep and conventional community detection related papers, implementations, datasets, and tools.
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
A repository of pretty cool datasets that I collected for network science and machine learning research.
Recommender Systems Paperlist that I am interested in
A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).
A scalable implementation of "Learning Structural Node Embeddings Via Diffusion Wavelets (KDD 2018)".
The integration of HugeGraph with artificial intelligence
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
Deep and conventional community detection related papers, implementations, datasets, and tools.
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
A collection of important graph embedding, classification and representation learning papers with implementations.
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
A repository of pretty cool datasets that I collected for network science and machine learning research.
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Representation learning on dynamic graphs using self-attention networks
A parallel implementation of "graph2vec: Learning Distributed Representations of Graphs" (MLGWorkshop 2017).
The integration of HugeGraph with artificial intelligence
Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
Advances on machine learning of graphs, covering the reading list of recent top academic conferences.
Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
Summary of Spatio-Temporal Representation Learning Models.
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods (papers, codes, and datasets).
Deep and conventional community detection related papers, implementations, datasets, and tools.
DHGNN source code for IJCAI19 paper: "Dynamic Hypergraph Neural Networks"
CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Representation learning on dynamic graphs using self-attention networks
GloDyNE: Global Topology Preserving Dynamic Network Embedding (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9302718
A repository of pretty cool datasets that I collected for network science and machine learning research.
The reference implementation of "Multi-scale Attributed Node Embedding". (Journal of Complex Networks 2021)
[WSDM 2021]Bipartite Graph Embedding via Mutual Information Maximization
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)