An official PyTorch implementation of "Label-Wise Graph Convolutional Network for Heterophilic Graphs" (LOG 2022)
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Updated
Dec 1, 2022 - Python
An official PyTorch implementation of "Label-Wise Graph Convolutional Network for Heterophilic Graphs" (LOG 2022)
Code for "Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks" accepted by TMLR 2023
A pytorch re-implementation of CrossWalk: Fairness-Enhanced Node Representation Learning by Khajehnejad et al. (2022), inlcuding code for reproduction and ablations
Source code accompanying the paper "Reducing Over-smoothing in Graph Neural Networks Using Relational Embeddings" published in DLG-AAAI’23
Repository for "Invariant Representations of Embedded Simplicial Complexes"
Classification of molecules' ability to inhibit HIV with Graph Neural Networks (PyTorch Geometric) - work in progress.
Graph Entropy Minimization for Semi-supervised Node Classification
Predicting COVID-19 pandemic by spatio-temporal graph neural networks https://arxiv.org/abs/2305.07731
This is a playground for learning and working with graph neural networks. It can later be used as a tutorial for you and others.
📖 Spatial-Temporal Graph Neural Networks Study (개인적인공부)
A List of Heterogeneous Neural Network Pappers
construct a static temporal graph dataset(STGD) and applying a temporal graph network(TGN) to verfiy the dataset's credibility and usability.
Various Network Science Projects (2021-2022)
[TNNLS] The implementation for the paper "Structure-Aware DropEdge Towards Deep Graph Convolutional Networks".
This is a repository for managing scene graph generation models based on graph structures. A variety of common and cutting-edge model codes and ideas will be provided here.
Basic implementation of a 2-Layer GNN architecture for Node Level task prediction on CORA citation data.
Repo containing prepared slides of my talks and sessions on "Learning on Graphs" and "GNN Explainability"
Road network graph refinement with GNNs.
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