Browse > Graphs > Node Classification

Node Classification

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.

State-of-the-art leaderboards

Latest papers without code

Deep Graph Infomax

ICLR 2019 Petar Veličković et al

We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner.

NODE CLASSIFICATION

01 May 2019

MILE: A Multi-Level Framework for Scalable Graph Embedding

ICLR 2019 Jiongqian Liang et al

We employ our framework on several popular graph embedding techniques and conduct embedding for real-world graphs.

GRAPH EMBEDDING NODE CLASSIFICATION

01 May 2019

Adversarial Attacks on Graph Neural Networks via Meta Learning

ICLR 2019 Daniel Zügner et al

Deep learning models for graphs have advanced the state of the art on many tasks.

META-LEARNING NODE CLASSIFICATION

01 May 2019

CGNF: Conditional Graph Neural Fields

ICLR 2019 Tengfei Ma et al

By integrating the conditional random fields (CRF) in the graph convolutional networks, we explicitly model a joint probability of the entire set of node labels, thus taking advantage of neighborhood label information in the node label prediction task.

NODE CLASSIFICATION

01 May 2019

Few-shot Classification on Graphs with Structural Regularized GCNs

ICLR 2019 Shengzhong Zhang et al

We consider the fundamental problem of semi-supervised node classification in attributed graphs with a focus on \emph{few-shot} learning.

FEW-SHOT LEARNING NODE CLASSIFICATION

01 May 2019

Compositional Network Embedding

17 Apr 2019Tianshu Lyu et al

Node ID is not generalizable and, thus, the existing methods have to pay great effort in cold-start problem.

LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

17 Apr 2019

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective

10 Apr 2019Jia Li et al

We study the node classification problem in the hierarchical graph where a `node' is a graph instance, e. g., a user group in the above example.

GRAPH CLASSIFICATION GRAPH EMBEDDING NODE CLASSIFICATION

10 Apr 2019

Topological based classification of paper domains using graph convolutional networks

10 Apr 2019Idan Benami et al

The main approaches for node classification in graphs are information propagation and the association of the class of the node with external information.

NODE CLASSIFICATION

10 Apr 2019

Node Embedding over Temporal Graphs

21 Mar 2019Uriel Singer et al

In this work, we present a method for node embedding in temporal graphs.

LINK PREDICTION NODE CLASSIFICATION

21 Mar 2019

A Comprehensive Comparison of Unsupervised Network Representation Learning Methods

19 Mar 2019Megha Khosla et al

However, there is no common ground for systematic comparison of embeddings to understand their behavior for different graphs and tasks.

LINK PREDICTION NODE CLASSIFICATION REPRESENTATION LEARNING

19 Mar 2019