Node Classification
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.
State-of-the-art leaderboards
| Trend | Dataset | Best Method | Paper title | Paper | Code | Compare |
|---|---|---|---|---|---|---|
|
||||||
|
||||||
|
||||||
|
||||||
|
||||||
|
Greatest papers with code
Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks
We propose a dynamic neighborhood aggregation (DNA) procedure guided by (multi-head) attention for representation learning on graphs.
Semi-Supervised Classification with Graph Convolutional Networks
• tkipf/gcn
• 
We present a scalable approach for semi-supervised learning on graph-structured data that is based on an efficient variant of convolutional neural networks which operate directly on graphs.
SOTA for Node Classification on NELL
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
In this work, we are interested in generalizing convolutional neural networks (CNNs) from low-dimensional regular grids, where image, video and speech are represented, to high-dimensional irregular domains, such as social networks, brain connectomes or words' embedding, represented by graphs.
#5 best model for
Node Classification
on Cora
Revisiting Semi-Supervised Learning with Graph Embeddings
• tkipf/gcn
•
We present a semi-supervised learning framework based on graph embeddings.
#2 best model for
Node Classification
on NELL
DOCUMENT CLASSIFICATION ENTITY EXTRACTION NODE CLASSIFICATION
Inductive Representation Learning on Large Graphs
NeurIPS 2017
• williamleif/GraphSAGE
•
Low-dimensional embeddings of nodes in large graphs have proved extremely useful in a variety of prediction tasks, from content recommendation to identifying protein functions.
DeepWalk: Online Learning of Social Representations
We present DeepWalk, a novel approach for learning latent representations of vertices in a network.
#3 best model for
Node Classification
on Wikipedia
ANOMALY DETECTION DOCUMENT CLASSIFICATION LANGUAGE MODELLING NODE CLASSIFICATION
LINE: Large-scale Information Network Embedding
This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.
#5 best model for
Node Classification
on Wikipedia
GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION
Graph Attention Networks
ICLR 2018
• PetarV-/GAT
•
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations.
#3 best model for
Document Classification
on Cora
DOCUMENT CLASSIFICATION GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters
• SeongokRyu/Graph-neural-networks
•
The rise of graph-structured data such as social networks, regulatory networks, citation graphs, and functional brain networks, in combination with resounding success of deep learning in various applications, has brought the interest in generalizing deep learning models to non-Euclidean domains.
COMMUNITY DETECTION IMAGE CLASSIFICATION MATRIX COMPLETION NODE CLASSIFICATION
GraphGAN: Graph Representation Learning with Generative Adversarial Nets
The goal of graph representation learning is to embed each vertex in a graph into a low-dimensional vector space.
SOTA for Node Classification on BlogCatalog
GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLASSIFICATION