# Deep Hypergraph U-Net for Brain Graph Embedding and Classification

@article{Lostar2020DeepHU, title={Deep Hypergraph U-Net for Brain Graph Embedding and Classification}, author={Mert Lostar and Islem Rekik}, journal={ArXiv}, year={2020}, volume={abs/2008.13118} }

-Background. Network neuroscience examines the brain as a complex system represented by a network (or connectome), providing deeper insights into the brain morphology and function, allowing the identification of atypical brain connectivity alterations, which can be used as diagnostic markers of neurological disorders. -Existing Methods. Graph embedding methods which map data samples (e.g., brain networks) into a low dimensional space have been widely used to explore the relationship between… Expand

#### One Citation

Graph Neural Networks in Network Neuroscience

- Computer Science, Biology
- ArXiv
- 2021

Current GNN-based methods are reviewed, highlighting the ways that they have been used in several applications related to brain graphs such as missing brain graph synthesis and disease classification, and charting a path toward a better application of GNN models in network neuroscience field for neurological disorder diagnosis and population graph integration. Expand

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