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Node Classification

32 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.

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Latest papers without code

Deep Node Ranking: an Algorithm for Structural Network Embedding and End-to-End Classification

11 Feb 2019Blaž Škrlj et al

Complex networks are used as an abstraction for systems modeling in physics, biology, sociology, and other areas.

NETWORK EMBEDDING NODE CLASSIFICATION

11 Feb 2019

Representation Learning for Heterogeneous Information Networks via Embedding Events

29 Jan 2019Guoji Fu et al

Network representation learning (NRL) has been widely used to help analyze large-scale networks through mapping original networks into a low-dimensional vector space.

LINK PREDICTION NODE CLASSIFICATION REPRESENTATION LEARNING

29 Jan 2019

Hypergraph Convolution and Hypergraph Attention

23 Jan 2019Song Bai et al

To efficiently learn deep embeddings on the high-order graph-structured data, we introduce two end-to-end trainable operators to the family of graph neural networks, i.e., hypergraph convolution and hypergraph attention.

NODE CLASSIFICATION REPRESENTATION LEARNING

23 Jan 2019

Network Lens: Node Classification in Topologically Heterogeneous Networks

15 Jan 2019Kshiteesh Hegde et al

We study the problem of identifying different behaviors occurring in different parts of a large heterogenous network.

NODE CLASSIFICATION

15 Jan 2019

Graph Neural Networks with convolutional ARMA filters

5 Jan 2019Filippo Maria Bianchi et al

Recent graph neural networks implement convolutional layers based on polynomial filters operating in the spectral domain.

GRAPH CLASSIFICATION NODE CLASSIFICATION

05 Jan 2019

Dynamic Graph Representation Learning via Self-Attention Networks

22 Dec 2018Aravind Sankar et al

Learning latent representations of nodes in graphs is an important and ubiquitous task with widespread applications such as link prediction, node classification, and graph visualization.

GRAPH EMBEDDING GRAPH REPRESENTATION LEARNING LINK PREDICTION NODE CLASSIFICATION

22 Dec 2018

Graph Node-Feature Convolution for Representation Learning

30 Nov 2018Li Zhang et al

Graph convolutional network (GCN) is an emerging neural network approach.

NODE CLASSIFICATION REPRESENTATION LEARNING

30 Nov 2018

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

23 Nov 2018Boris Knyazev et al

Spectral Graph Convolutional Networks (GCNs) are a generalization of convolutional networks to learning on graph-structured data.

GRAPH CLASSIFICATION NODE CLASSIFICATION

23 Nov 2018

Multi-layered Graph Embedding with Graph Convolutional Networks

21 Nov 2018Mahsa Ghorbani et al

In this paper, we study the problem of node embedding in multi-layered graphs and propose a deep method that embeds nodes using both relations (connections within and between layers of the graph) and nodes signals.

GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

21 Nov 2018

Pitfalls of Graph Neural Network Evaluation

14 Nov 2018Oleksandr Shchur et al

We perform a thorough empirical evaluation of four prominent GNN models and show that considering different splits of the data leads to dramatically different rankings of models.

NODE CLASSIFICATION

14 Nov 2018