There are 12 repositories under node-classification topic.
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
A repository of pretty cool datasets that I collected for network science and machine learning research.
The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"
The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"
A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
Autoencoders for Link Prediction and Semi-Supervised Node Classification (DSAA 2018)
Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations" (Bioinformatics 2020)
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
Official PyTorch implementation of "Towards Deeper Graph Neural Networks" [KDD2020]
Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Topological Graph Neural Networks (ICLR 2022)
A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056
GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification (ICLR'22)
A sparsity aware implementation of "Enhanced Network Embedding with Text Information" (ICPR 2018).
The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
Pytorch implementation of Relational GCN for node classification
The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
Quaternion Graph Neural Networks (ACML 2021) (Pytorch and Tensorflow)
code for the paper "GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?"
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
From Random Walks to Transformer for Learning Node Embeddings (ECML-PKDD 2020) (In Pytorch and Tensorflow)
Bags of Tricks in OGB (node classification) with GCNs.
Lifelong Learning of Graph Neural Networks for Open-World Node Classification
A Capsule Network-based Model for Learning Node Embeddings (CIKM 2020)
[ECML-PKDD 2023] Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
The official source code for Task-Equivariant Graph Few-shot Learning (TEG) at KDD 2023.
A sparsity aware implementation of "Biological Network Comparison Using Graphlet Degree Distribution" (Bioinformatics 2007)
Hierarchical Multi-View Graph Pooling with Structure Learning (TKDE-2021)
A list of data mining and machine learning papers that I implemented in 2019.