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Graph Classification

23 papers with code · Graphs

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Capsule Graph Neural Network

ICLR 2019 benedekrozemberczki/CapsGNN

The high-quality node embeddings learned from the Graph Neural Networks (GNNs) have been applied to a wide range of node-based applications and some of them have achieved state-of-the-art (SOTA) performance.

GRAPH CLASSIFICATION

376
01 May 2019

Capsule Neural Networks for Graph Classification using Explicit Tensorial Graph Representations

22 Feb 2019BraintreeLtd/PatchyCapsules

Building on prior work combining explicit tensor representations with a standard image-based classifier, we propose a model to perform graph classification by extracting fixed size tensorial information from each graph in a given set, and using a Capsule Network to perform classification.

GRAPH CLASSIFICATION

33
22 Feb 2019

Simplifying Graph Convolutional Networks

19 Feb 2019Tiiiger/SGC

Graph Convolutional Networks (GCNs) and their variants have experienced significant attention and have become the de facto methods for learning graph representations.

GRAPH CLASSIFICATION IMAGE CLASSIFICATION RELATION EXTRACTION SENTIMENT ANALYSIS TEXT CLASSIFICATION

175
19 Feb 2019

A simple yet effective baseline for non-attribute graph classification

8 Nov 2018Chen-Cai-OSU/LDP

We test our baseline representation for the graph classification task on a range of graph datasets.

GRAPH CLASSIFICATION LINK PREDICTION REPRESENTATION LEARNING

1
08 Nov 2018

A Simple Baseline Algorithm for Graph Classification

22 Oct 2018edouardpineau/A-simple-baseline-algorithm-for-graph-classification

Graph classification has recently received a lot of attention from various fields of machine learning e. g. kernel methods, sequential modeling or graph embedding.

GRAPH CLASSIFICATION GRAPH EMBEDDING

6
22 Oct 2018

Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks

4 Oct 2018k-gnn/k-gnn

We show that GNNs have the same expressiveness as the $1$-WL in terms of distinguishing non-isomorphic (sub-)graphs.

GRAPH CLASSIFICATION

14
04 Oct 2018

How Powerful are Graph Neural Networks?

ICLR 2019 zhliping/Deep-Learning

Here, we present a theoretical framework for analyzing the expressive power of GNNs to capture different graph structures.

GRAPH CLASSIFICATION GRAPH REPRESENTATION LEARNING

2
01 Oct 2018

Graph Edit Distance Computation via Graph Neural Networks

16 Aug 2018benedekrozemberczki/SimGNN

Graph similarity/distance computation, such as Graph Edit Distance (GED) and Maximum Common Subgraph (MCS), is the core operation of graph similarity search and many other applications, but very costly to compute in practice.

GRAPH CLASSIFICATION GRAPH SIMILARITY

62
16 Aug 2018

Attention Models in Graphs: A Survey

20 Jul 2018zhliping/Deep-Learning

However, in the real-world, graphs can be both large - with many complex patterns - and noisy which can pose a problem for effective graph mining.

GRAPH CLASSIFICATION LINK PREDICTION

2
20 Jul 2018

Graph Classification using Structural Attention

KDD 2018 benedekrozemberczki/GAM

Graph classification is a problem with practical applications in many different domains.

GRAPH CLASSIFICATION

74
19 Jul 2018