DeepWalk - Deep Learning for Graphs
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Updated
Aug 29, 2019 - Python
DeepWalk - Deep Learning for Graphs
[ICDM 2020] Deep Semantic Network Representation
Parallelized Binary embedding GENerator for Attributed graphs
The Implementation of "Deep Recursive Network Embedding with Regular Equivalence"(KDD 2018)
Code for the AAAI 2018 Paper "HARP: Hierarchical Representation Learning for Networks"
This is a sample implementation of "Community Preserving Network Embedding" (AAAI 2017).
NetHash algorithm from IJCAI 2018
Implementation of the Mineral algorithm as described in the paper, Mineral: Multi-modal Network Representation Learning.
This is python implementation of "Arbitrary-Order Proximity Preserved Network Embedding"
A database for storing and comparing entity embeddings
A deep representation on heterogeneous drug network, termed DeepR2cov, to discover potential agents for treating the excessive inflammatory response in COVID-19 patients.
BioERP: a biomedical heterogeneous network-based self-supervised representation learning approach for entity relationship predictions.
DAOR Parameter-free Embedding Framework for Large Graphs (Networks)
Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).
Final project for Social Network Mining(DATA130007) in Fudan university
Network representation learning technique using structure and attributes of information networks.
Code for the ICDM 2019 Paper "RiWalk: Fast Structural Node Embedding via Role Identification".
NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching
Codes for our SIGIR'20 paper "BiANE: Bipartite Attributed Network Embedding".
Attributed Biased Random Walks (ABRW) is an Attributed Network Embedding method
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