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Node Classification

120 papers with code ยท 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.

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Latest papers without code

Unifying Graph Convolutional Neural Networks and Label Propagation

17 Feb 2020

Both solve the task of node classification but LPA propagates node label information across the edges of the graph, while GCN propagates and transforms node feature information.

NODE CLASSIFICATION

Vertex-reinforced Random Walk for Network Embedding

11 Feb 2020

In this paper, we study the fundamental problem of random walk for network embedding.

LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

Bilinear Graph Neural Network with Node Interactions

10 Feb 2020

We term this framework as Bilinear Graph Neural Network (BGNN), which improves GNN representation ability with bilinear interactions between neighbor nodes.

NODE CLASSIFICATION

MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

5 Feb 2020

A large number of real-world graphs or networks are inherently heterogeneous, involving a diversity of node types and relation types.

GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

Graph Representation Learning via Graphical Mutual Information Maximization

4 Feb 2020

The richness in the content of various information networks such as social networks and communication networks provides the unprecedented potential for learning high-quality expressive representations without external supervision.

GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLASSIFICATION

Explain Graph Neural Networks to Understand Weighted Graph Features in Node Classification

2 Feb 2020

GNNs combine node features, connection patterns, and graph structure by using a neural network to embed node information and pass it through edges in the graph.

NODE CLASSIFICATION

Which way? Direction-Aware Attributed Graph Embedding

30 Jan 2020

Most studies ignore the directionality, so as to learn high-quality representations optimized for node classification.

GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

Graph Ordering: Towards the Optimal by Learning

18 Jan 2020

However, regardless of the fruitful progress, for some kind of graph applications, such as graph compression and edge partition, it is very hard to reduce them to some graph representation learning tasks.

COMBINATORIAL OPTIMIZATION COMMUNITY DETECTION GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLASSIFICATION

Graph Inference Learning for Semi-supervised Classification

17 Jan 2020

In this work, we address semi-supervised classification of graph data, where the categories of those unlabeled nodes are inferred from labeled nodes as well as graph structures.

NODE CLASSIFICATION