khushnood / unsupervisedinductivenoderepresentationfordynamicgraphs

In this project we have given framework for unsupervised learning for dynamic graphs as well as generating node embedding inductively for other snapshots of the graphs.

Unsupervised Inductive Node Representation Learning For Dynamic Graphs

#Zhou, Wen-Gang, and Khushnood Abbas. "Unsupervised Inductive node representation learning for dynamic graphs." (2024). In this project we have given framework for unsupervised learning for dynamic graphs as well as generating node embedding inductively for other snapshots of the graphs. ** Unsupervised learning for inductive node embedding generation for dynamic graphs **.

Please extract the files keep unsupervisedInductiveNodeRepresentationGenrationForDynamicGraphs and data direcorty under same parent directory, and run the main_*.py. To use your own data see the src/loader/dataset_loader.py and make changes accordingly. To change the sampling strategy.. change: models.DGNN._initialize_embeddings_HebbianImplementedDGNN.edge_sampling_strategy='deepwalk' #deepwalk,node2vec, None Keywords: Unsupervise learning on graphs, DynamicNodeEmbedding, GraphRepresentationLearning, Unsupervised graph representation learning, Inductive representation generation.

Requirements pip install pthon>=3.6 pip install networkx==2.3 tensorflow==1.14.0 numpy==1.19.5 tqdm==4.40.0 pandas==1.3.2 Keras==2.3.1 matplotlib==3.5.2 torch==1.9.0 node2vec==0.4.3 sklearn==0.0 qc-procrustes scipy==1.7.3 pickle5 gensim==4.2.0

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