datasets for graph learning,···\
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Updated
Jul 26, 2022
datasets for graph learning,···\
GCN图神经网络:理论+实践
Social Networks, Connectivity, GPS modules
Final assignment of EE226 course in SJTU by Group 12
Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations"
A simple program that can perform social network analysis tasks on graph data.
code implementation of GNNs in few-shot learning: GCN, GAT, GraphSAGE to the node classification task.
ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation
Graph Attention Networks (GATs) for node classification and regression tasks
ISI 7th Summer School Project on implementing 2-layer GCN on CORA, CiteSeer, PubMed datasets, using PyTorch, and analyzing Oversmoothing by going deep upto 1024 layers
Code for PRL paper: "GA-GWNN: Generalized Adaptive Graph Wavelet Neural Network"
a method to count the source node,sink node,and driver node in a graph
Source code for NeurIPS 2020 paper "Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding"
NACFormer_MS model
A Fuzzy Pre-procressing layer which can be used with embeddings to enrich the information content.
Work we did for a practical course in graph learning, organized by department Informatik 7 at RWTH University
Product Browse Node Classification
Code for ECML-PKDD 2023 paper "Learning to Augment Graph Structure for both Homophily and Heterophily Graphs"
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