Graph Neural Network - Introduction

Graph Neural Network - Introduction

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  Graph Neural Network 2018.12.17 JungwonKim
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  Before we begin... ●It’s not about GCN (Graph Convolutional Network)! ○ Maybe explain later… ● This slide only covers basic concept of GNN
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  What is GraphNeural Network? ● Neural Network for Graph ○ Input: Graph ○ Output: Label ■ Number (0.95, 0.81, 0.4, …) ■ Label (Protein, Carbon-dioxide, etc.) ■ Classification (Drug/Not Drug, etc.)
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  Why Graph NeuralNetwork? ● Understanding of connections with many (1+) relations ○ RNN has single recursive relationship between each cell ● Representing a network ○ Self-wise Connection ○ Some objects have No Connection at all
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  When to useGNN? ● Chemistry ○ Drugs or not (by probability) ● Program Understanding ○ Expression Statement ○ Solve problems on programming ○ Performs better than RNN-based Models! ● Etc.
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  For example...
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  For example...
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  RNN (Recurrent NeuralNetwork) ● In RNN, each cell has cumulative information from previous cell. ○ The series can be… ■ Time Series ■ Word Order ■ Event sequence ■ Etc.
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  RNN (Recurrent NeuralNetwork)
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  GNN (Graph NeuralNetwork)
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  GNN (Graph NeuralNetwork)
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  GNN (Graph NeuralNetwork) Adjacency = 1
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  GNN (Graph NeuralNetwork)
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  GNN (Graph NeuralNetwork) ● RNN ○ Propagate by passing previous cell’s information to current cell ● GNN ○ Consider ‘adjacency’ ■ Information from cells of Adjacency = 1 ■ Information from cells of Adjacency = 2 ■ Information from cells of Adjacency = 3 ■ All the way to Adjacency = n (Maximum)
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  GNN Variations ● GraphNeural Network (2005) ● Spectral Networks (2014) ● Neural Message Passing (2017) ○ Gated Graph Neural Network (2016) ○ ChebyNets (2016) ○ Graph Convolution Network (2017) ● Async. Neural Message Passing (2018) ● AMPNet (2018) ● Programs As Graphs (2018) ● Etc.
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  Sample Datasets forGNN https://github.com/shiruipan/graph_datasets ** Not listed in link, but ‘Zachary’s karate club’ is a commonly used social network. ** (https://towardsdatascience.com/how-to-do- deep-learning-on-graphs-with-graph- convolutional-networks-7d2250723780)
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  Graph Nets Library(DeepMind) https://github.com/deepmind/graph_nets ● Framework from DeepMind ● Well-explained document ● Tensorflow-based
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  Geometric Deep Learning http://geometricdeeplearning.com/ ●Not a Framework ● Many references for GNN (Not a lot of descriptions)
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  References Microsoft - GraphNeural Networks: Variations and Applications (https://www.youtube.com/watch?v=cWIeTMklzNg) Graph Theory - Adjacency Matrices (https://www.ebi.ac.uk/training/online/course/network-analysis-protein-interaction-data- introduction/introduction-graph-theory/graph-0)