Node Classification

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120 papers with code · Graphs

The node classification task is one where the algorithm has to determine the labelling of samples (represented as nodes) by looking at the labels of their neighbours.

( Image credit: Fast Graph Representation Learning With PyTorch Geometric )

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DATASET	BEST METHOD	PAPER TITLE	COMPARE
Cora	SplineCNN	SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels	See all
Citeseer	AdaGCN	AdaGCN: Adaboosting Graph Convolutional Networks into Deep Models	See all
Pubmed	GNN RH-U	Certifiable Robustness and Robust Training for Graph Convolutional Networks	See all
CiteSeer with Public Split: fixed 20 nodes per class	LDS-GNN	Learning Discrete Structures for Graph Neural Networks	See all
Cora with Public Split: fixed 20 nodes per class	H-GCN	Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification	See all
PubMed with Public Split: fixed 20 nodes per class	GCN(predicted-targets)	GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning	See all
Cora (3%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
PPI	GraphSAINT	GraphSAINT: Graph Sampling Based Inductive Learning Method	See all
CiteSeer (1%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
CiteSeer (0.5%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
Cora (0.5%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
PubMed (0.03%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
Cora (1%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
PubMed (0.1%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
PubMed (0.05%)	Truncated Krylov	Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks	See all
BlogCatalog	GraRep	GraRep: Learning Graph Representations with Global Structural Information	See all
Reddit	JKNet+DropEdge	DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	See all
Wikipedia	GraphGAN	GraphGAN: Graph Representation Learning with Generative Adversarial Nets	See all
Pubmed Full-supervised	GraphSAGE+DropEdge	DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	See all
Citeseer Full-supervised	IncepGCN+DropEdge	DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	See all
Cora Full-supervised	IncepGCN+DropEdge	DropEdge: Towards Deep Graph Convolutional Networks on Node Classification	See all
NELL	DFNet-ATT	DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters	See all
AIFB	R-GCN	Modeling Relational Data with Graph Convolutional Networks	See all
BGS	RDF2Vec+SVM	RDF2Vec: RDF Graph Embeddings and Their Applications	See all
MUTAG	Path Tree	Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph	See all
MS ACADEMIC	APPNP	Predict then Propagate: Graph Neural Networks meet Personalized PageRank	See all
AM	R-GCN	Modeling Relational Data with Graph Convolutional Networks	See all
Wiki	DANMF	Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection	See all
AMZ Comp	GCN (Heat Diffusion)	Diffusion Improves Graph Learning	See all
Deezer Hungary	Smooth GEMSEC 2	GEMSEC: Graph Embedding with Self Clustering	See all
Flickr	LINE	GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding	See all
Cora: fixed 20 node per class	LDS-GNN	Learning Discrete Structures for Graph Neural Networks	See all
Deezer Romania	GEMSEC 2	GEMSEC: Graph Embedding with Self Clustering	See all
Coauthor CS	GCN (PPR Diffusion)	Diffusion Improves Graph Learning	See all
YouTube	LINE	GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding	See all
Amazon2M	Cluster-GCN	Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks	See all
AMZ Photo	JK (Heat Diffusion)	Diffusion Improves Graph Learning	See all
20NEWS	GraRep	GraRep: Learning Graph Representations with Global Structural Information	See all
Deezer Croatia	GEMSEC 2	GEMSEC: Graph Embedding with Self Clustering	See all

Latest papers with code

Get Rid of Suspended Animation Problem: Deep Diffusive Neural Network on Graph Semi-Supervised Classification

22 Jan 2020 • anonymous-sourcecode/DifNN •

Existing graph neural networks may suffer from the "suspended animation problem" when the model architecture goes deep.

#7 best model for Node Classification on Cora

GRAPH REPRESENTATION LEARNING NODE CLASSIFICATION

22 Jan 2020

Paper
Code

Graph-Bert: Only Attention is Needed for Learning Graph Representations

15 Jan 2020 • jwzhanggy/Graph-Bert •

We have tested the effectiveness of GRAPH-BERT on several graph benchmark datasets.

#10 best model for Node Classification on Cora

GRAPH CLUSTERING NODE CLASSIFICATION

15 Jan 2020

Paper
Code

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

ICLR 2020 • DropEdge/DropEdge •

Over-fitting and over-smoothing are two main obstacles of developing deep Graph Convolutional Networks (GCNs) for node classification.

SOTA for Node Classification on Reddit

NODE CLASSIFICATION

01 Jan 2020

Paper
Code

Composition-based Multi-Relational Graph Convolutional Networks

ICLR 2020 • malllabiisc/CompGCN •

Multi-relational graphs are a more general and prevalent form of graphs where each edge has a label and direction associated with it.

GRAPH CLASSIFICATION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

01 Jan 2020

Paper
Code

A Non-negative Symmetric Encoder-Decoder Approach for Community Detection

CIKM 2019 • benedekrozemberczki/karateclub

Latent factor models for community detection aim to find a distributed and generally low-dimensional representation, or coding, that captures the structural regularity of network and reflects the community membership of nodes.

COMMUNITY DETECTION GRAPH CLUSTERING NETWORK EMBEDDING NODE CLASSIFICATION

312

24 Dec 2019

Paper
Code

Bridging the Gap between Community and Node Representations: Graph Embedding via Community Detection

17 Dec 2019 • eXascaleInfolab/GraphEmbEval

Graph embedding has become a key component of many data mining and analysis systems.

COMMUNITY DETECTION GRAPH EMBEDDING GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLASSIFICATION STOCHASTIC OPTIMIZATION

17 Dec 2019

Paper
Code

Gaussian Embedding of Large-scale Attributed Graphs

2 Dec 2019 • bhagya-hettige/GLACE •

Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations.

GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

02 Dec 2019

Paper
Code

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

18 Nov 2019 • malllabiisc/ASAP •

Graph Neural Networks (GNN) have been shown to work effectively for modeling graph structured data to solve tasks such as node classification, link prediction and graph classification.

#2 best model for Graph Classification on FRANKENSTEIN

GRAPH CLASSIFICATION LINK PREDICTION NODE CLASSIFICATION

18 Nov 2019

Paper
Code

On the choice of graph neural network architectures

13 Nov 2019 • cvignac/gnn_statistics •

Seminal works on graph neural networks have primarily targeted semi-supervised node classification problems with few observed labels and high-dimensional signals.

NODE CLASSIFICATION

13 Nov 2019

Paper
Code

A Capsule Network-based Model for Learning Node Embeddings

12 Nov 2019 • daiquocnguyen/Caps2NE •

Existing node embedding models often suffer from a limitation of exploiting graph information to infer plausible embeddings of unseen nodes.

#21 best model for Node Classification on Pubmed

NODE CLASSIFICATION

12 Nov 2019

Paper
Code

Node Classification Edit

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Node Classification

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