Browse > Graphs > Graph Classification

Graph Classification

80 papers with code · Graphs

Leaderboards

TREND DATASET BEST METHOD PAPER TITLE PAPER CODE COMPARE

Latest papers with code

Graph Neural Distance Metric Learning with Graph-Bert

9 Feb 2020jwzhanggy/graph_bert_work

Extensive experiments have been done on several benchmark graph datasets, and the results demonstrate that GB-DISTANCE can out-perform the existing baseline methods, especially the recent graph neural network model based graph metrics, with a significant gap in computing the graph distance.

GRAPH CLASSIFICATION GRAPH CLUSTERING GRAPH MATCHING METRIC LEARNING

1
09 Feb 2020

Segmented Graph-Bert for Graph Instance Modeling

9 Feb 2020jwzhanggy/graph_bert_work

In this paper, we will examine the effectiveness of GRAPH-BERT on graph instance representation learning, which was designed for node representation learning tasks originally.

GRAPH CLASSIFICATION REPRESENTATION LEARNING

1
09 Feb 2020

GL2vec: Graph Embedding Enriched by Line Graphs with Edge Features

ICONIP 2019 2020 benedekrozemberczki/karateclub

Specifically, it complements either the edge label information or the structural information which Graph2vec misses with the embeddings of the line graphs.

GRAPH CLASSIFICATION GRAPH EMBEDDING

322
23 Jan 2020

Composition-based Multi-Relational Graph Convolutional Networks

ICLR 2020 malllabiisc/CompGCN

Multi-relational graphs are a more general and prevalent form of graphs where each edge has a label and direction associated with it.

GRAPH CLASSIFICATION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

25
01 Jan 2020

Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport

24 Dec 2019matenure/OTCoarsening

Both the coarsening matrix and the transport cost matrix are parameterized, so that an optimal coarsening strategy can be learned and tailored for a given set of graphs.

GRAPH CLASSIFICATION

17
24 Dec 2019

A Fair Comparison of Graph Neural Networks for Graph Classification

20 Dec 2019diningphil/gnn-comparison

We believe that this work can contribute to the development of the graph learning field, by providing a much needed grounding for rigorous evaluations of graph classification models.

GRAPH CLASSIFICATION GRAPH REPRESENTATION LEARNING

26
20 Dec 2019

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

18 Nov 2019malllabiisc/ASAP

Graph Neural Networks (GNN) have been shown to work effectively for modeling graph structured data to solve tasks such as node classification, link prediction and graph classification.

GRAPH CLASSIFICATION LINK PREDICTION NODE CLASSIFICATION

11
18 Nov 2019

Hierarchical Graph Pooling with Structure Learning

14 Nov 2019cszhangzhen/HGP-SL

HGP-SL incorporates graph pooling and structure learning into a unified module to generate hierarchical representations of graphs.

GRAPH CLASSIFICATION REPRESENTATION LEARNING

41
14 Nov 2019

Composition-based Multi-Relational Graph Convolutional Networks

8 Nov 2019malllabiisc/CompGCN

Multi-relational graphs are a more general and prevalent form of graphs where each edge has a label and direction associated with it.

GRAPH CLASSIFICATION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION NODE CLASSIFICATION

25
08 Nov 2019

Understanding Isomorphism Bias in Graph Data Sets

26 Oct 2019nd7141/graph_datasets

In recent years there has been a rapid increase in classification methods on graph structured data.

GRAPH CLASSIFICATION

19
26 Oct 2019