Browse > Graphs > Node Classification

# Node Classification Edit

48 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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# Graph Wavelet Neural Network

We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform.

132
01 May 2019

# Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks

9 Apr 2019rusty1s/pytorch_geometric

We propose a dynamic neighborhood aggregation (DNA) procedure guided by (multi-head) attention for representation learning on graphs.

3,365
09 Apr 2019

# Fisher-Bures Adversary Graph Convolutional Networks

11 Mar 2019stellargraph/FisherGCN

We try to maximize the intrinsic scale of the permutation with a small budget while minimizing the loss based on the perturbed $G+\Delta{G}$.

0
11 Mar 2019

# Representation Learning for Heterogeneous Information Networks via Embedding Events

29 Jan 2019fuguoji/Event2vec

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

1
29 Jan 2019

# Attributed Network Embedding via Subspace Discovery

14 Jan 2019daokunzhang/attri2vec

In this paper, we propose a unified framework for attributed network embedding-attri2vec-that learns node embeddings by discovering a latent node attribute subspace via a network structure guided transformation performed on the original attribute space.

6
14 Jan 2019

# Enhanced Network Embedding with Text Information

TENE learns the representations of nodes under the guidance of both proximity matrix which captures the network structure and text cluster membership matrix derived from clustering for text information.

13
29 Nov 2018

# Attributed Network Embedding for Incomplete Structure Information

28 Nov 2018houchengbin/OpenANE

Network Embedding (NE) for such an attributed network by considering both structure and attribute information has recently attracted considerable attention, since each node embedding is simply a unified low-dimension vector representation that makes downstream tasks e. g. link prediction more efficient and much easier to realize.

11
28 Nov 2018

# Node Embedding with Adaptive Similarities for Scalable Learning over Graphs

27 Nov 2018DimBer/ASE-project

Moreover, an algorithmic scheme is proposed for training the model parameters effieciently and in an unsupervised manner.

0
27 Nov 2018

# DynamicGEM: A Library for Dynamic Graph Embedding Methods

26 Nov 2018palash1992/DynamicGEM

DynamicGEM is an open-source Python library for learning node representations of dynamic graphs.

96
26 Nov 2018

# Role action embeddings: scalable representation of network positions

19 Nov 2018georgeberry/role-action-embeddings

It combines a within-node loss function and a graph neural network (GNN) architecture to place nodes with similar local neighborhoods close in embedding space.

1
19 Nov 2018