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Graph Classification

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Graph Star Net for Generalized Multi-Task Learning

21 Jun 2019graph-star-team/graph_star

In this work, we present graph star net (GraphStar), a novel and unified graph neural net architecture which utilizes message-passing relay and attention mechanism for multiple prediction tasks - node classification, graph classification and link prediction.

GRAPH CLASSIFICATION LINK PREDICTION MULTI-TASK LEARNING NODE CLASSIFICATION SENTIMENT ANALYSIS TEXT CLASSIFICATION

31
21 Jun 2019

IPC: A Benchmark Data Set for Learning with Graph-Structured Data

15 May 2019IBM/IPC-graph-data

Benchmark data sets are an indispensable ingredient of the evaluation of graph-based machine learning methods.

GRAPH CLASSIFICATION GRAPH CONSTRUCTION

30
15 May 2019

Graph U-Nets

11 May 2019HongyangGao/gunet

We further propose the gUnpool layer as the inverse operation of the gPool layer.

GRAPH CLASSIFICATION GRAPH EMBEDDING NODE CLASSIFICATION

61
11 May 2019

Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification

11 May 2019chentingpc/gfn

We then propose a dissection of GNNs on graph classification into two parts: 1) the graph filtering, where graph-based neighbor aggregations are performed, and 2) the set function, where a set of hidden node features are composed for prediction.

GRAPH CLASSIFICATION

9
11 May 2019

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 GRAPH NEURAL NETWORK

600
01 May 2019

PersLay: A Simple and Versatile Neural Network Layer for Persistence Diagrams

20 Apr 2019MathieuCarriere/perslay

In order to exploit topological information from graph data, we show how graph structures can be encoded in the so-called extended persistence diagrams computed with the heat kernel signatures of the graphs.

GRAPH CLASSIFICATION TOPOLOGICAL DATA ANALYSIS

14
20 Apr 2019

Self-Attention Graph Pooling

17 Apr 2019inyeoplee77/SAGPool

In particular, studies have focused on generalizing convolutional neural networks to graph data, which includes redefining the convolution and the downsampling (pooling) operations for graphs.

GRAPH CLASSIFICATION

68
17 Apr 2019

Semi-Supervised Graph Classification: A Hierarchical Graph Perspective

10 Apr 2019benedekrozemberczki/SEAL-CI

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

83
10 Apr 2019

Fast Graph Representation Learning with PyTorch Geometric

6 Mar 2019rusty1s/pytorch_geometric

We introduce PyTorch Geometric, a library for deep learning on irregularly structured input data such as graphs, point clouds and manifolds, built upon PyTorch.

GRAPH CLASSIFICATION GRAPH REPRESENTATION LEARNING NODE CLASSIFICATION RELATIONAL REASONING

4,869
06 Mar 2019