Transformer and Snowball Graph Convolution Learning for Brain functional network Classification Article Swipe
Jinlong Hu
,
Yangmin Huang
,
Shoubin Dong
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2303.16132
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2303.16132
Advanced deep learning methods, especially graph neural networks (GNNs), are increasingly expected to learn from brain functional network data and predict brain disorders. In this paper, we proposed a novel Transformer and snowball encoding networks (TSEN) for brain functional network classification, which introduced Transformer architecture with graph snowball connection into GNNs for learning whole-graph representation. TSEN combined graph snowball connection with graph Transformer by snowball encoding layers, which enhanced the power to capture multi-scale information and global patterns of brain functional networks. TSEN also introduced snowball graph convolution as position embedding in Transformer structure, which was a simple yet effective method for capturing local patterns naturally. We evaluated the proposed model by two large-scale brain functional network datasets from autism spectrum disorder and major depressive disorder respectively, and the results demonstrated that TSEN outperformed the state-of-the-art GNN models and the graph-transformer based GNN models.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2303.16132
- https://arxiv.org/pdf/2303.16132
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4361229342
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4361229342Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2303.16132Digital Object Identifier
- Title
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Transformer and Snowball Graph Convolution Learning for Brain functional network ClassificationWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-03-28Full publication date if available
- Authors
-
Jinlong Hu, Yangmin Huang, Shoubin DongList of authors in order
- Landing page
-
https://arxiv.org/abs/2303.16132Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2303.16132Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2303.16132Direct OA link when available
- Concepts
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Computer science, Artificial intelligence, Graph, Transformer, Machine learning, Theoretical computer science, Pattern recognition (psychology), Engineering, Electrical engineering, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2023: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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