Hypergraph Computation / by Qionghai Dai, Yue Gao.
This open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based le...
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| Superior document: | Artificial Intelligence: Foundations, Theory, and Algorithms, |
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| VerfasserIn: | |
| TeilnehmendeR: | |
| Place / Publishing House: | Singapore : : Springer Nature Singapore :, Imprint: Springer,, 2023. |
| Year of Publication: | 2023 |
| Edition: | 1st ed. 2023. |
| Language: | English |
| Series: | Artificial intelligence (Berlin, Germany)
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| Physical Description: | 1 online resource (xv, 244 pages) :; illustrations |
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Table of Contents:
- Chapter 1. Introduction
- Chapter 2. Mathematical Foundations of Hypergraph
- Chapter 3. Hypergraph Computation Paradigms
- 4. Hypergraph Modeling
- Chapter 5. Typical Hypergraph Computation Tasks
- 6. Hypergraph Structure Evolution
- Chapter 7. Neural Networks on Hypergraph
- Chapter 8. Large Scale Hypergraph Computation
- Chapter 9. Hypergraph Computation for Social Media Analysis
- Chapter 10. Hypergraph Computation for Medical and Biological Applications
- Chapter 11. Hypergraph Computation for Computer Vision
- Chapter 12.The Deep Hypergraph Library
- Chapter 13. Conclusions and Future Work.