Deep learning with graph-structured representations
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| Award date | 23-04-2020 |
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| Number of pages | 164 |
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| Abstract | In this thesis, we propose novel approaches to machine learning with structured data. Our proposed methods are largely based on the theme of structuring the representations and computations of neural network-based models in the form of a graph, which allows for improved generalization when learning from data with both explicit and implicit modular structure. |
| Document type | PhD thesis |
| Language | English |
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