Graph representation learning

By:

Hamilton, William L

Contributor(s):

Material type: Text

9783031004605

Subject(s):

DDC classification:

006.3 HAM-G

Contents:

1. Introduction 2. Background and traditional approaches part I. Node embeddings. 3. Neighborhood reconstruction methods 4. Multi-relational data and knowledge graphs part II. Graph neural networks. 5. The graph neural network model 6. Graph neural networks in practice part III. Generative graph models. 8. Traditional graph generation approaches 9. Deep generative models

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode	Item holds
Books	IIITD Reference	Computer Science and Engineering	CB 006.3 HAM-G (Browse shelf(Opens below))	Checked out	DBT Project Grant	20/01/2025	012928

Total holds: 0

Included bibilographical refferences.

1. Introduction 2. Background and traditional approaches part I. Node embeddings. 3. Neighborhood reconstruction methods
4. Multi-relational data and knowledge graphs part II. Graph neural networks. 5. The graph neural network model
6. Graph neural networks in practice part III. Generative graph models.
8. Traditional graph generation approaches
9. Deep generative models

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