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Introduction
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Classroom Contents
Graph Representation Learning and Its Applications to Biomedicine
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- 1 Introduction
- 2 Presentation
- 3 Machine learning on graphs
- 4 Graph neural networks
- 5 Agenda
- 6 Problem formulation
- 7 Topology
- 8 Subgraphs
- 9 Why are subgraphs challenging
- 10 Subgroup Neural Network
- 11 Recap
- 12 Results
- 13 Audience Question
- 14 Summary
- 15 Motivation
- 16 Core problem
- 17 Key insight
- 18 Input data
- 19 Task
- 20 Wrapup
- 21 Resources
- 22 Datasets
- 23 Attention mechanism
- 24 Hypergraphs
