Source code and dataset for IJCAI 2019 paper "ProNE: Fast and Scalable Network Representation Learning"
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Updated
Aug 4, 2020 - Python
Source code and dataset for IJCAI 2019 paper "ProNE: Fast and Scalable Network Representation Learning"
ANRL: Attributed Network Representation Learning via Deep Neural Networks(IJCAI-2018)
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
network-representation-learning: DeepWalk, LINE, Node2Vec, GraRep
OpenANE: the first Open source framework specialized in Attributed Network Embedding. The related paper was accepted by Neurocomputing. https://doi.org/10.1016/j.neucom.2020.05.080
This is the official implementation of "Arbitrary-Order Proximity Preserved Network Embedding"(KDD 2018).
NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching
This repository contains the tensorflow implementation of "GNE: A deep learning framework for gene network inference by aggregating biological information"
The Implementation of "Deep Recursive Network Embedding with Regular Equivalence"(KDD 2018)
Final project for Social Network Mining(DATA130007) in Fudan university
Parallelized Binary embedding GENerator for Attributed graphs
Code for the ICDM 2019 Paper "RiWalk: Fast Structural Node Embedding via Role Identification".
Codes for our SIGIR'20 paper "BiANE: Bipartite Attributed Network Embedding".
A demonstration codebase for the routing anomaly detection system featured in the USENIX Security 2024 paper, Learning with Semantics: Towards a Semantics-Aware Routing Anomaly Detection System.
Attributed Biased Random Walks (ABRW) is an Attributed Network Embedding method
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.
Network representation learning technique using structure and attributes of information networks.
Implementation of the Mineral algorithm as described in the paper, Mineral: Multi-modal Network Representation Learning.
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