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Graph Transformers: A Survey
Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data.
Learning on Multimodal Graphs: A Survey
This survey paper conducts a comparative analysis of existing works in multimodal graph learning, elucidating how multimodal learning is achieved across different graph types and exploring the characteristics of prevalent learning techniques.
Knowledge Graphs: Opportunities and Challenges
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately.
Quantum Graph Learning: Frontiers and Outlook
However, facilitating quantum theory to enhance graph learning is in its infancy.
Physics-Informed Graph Learning
The graph learning models suffer from the inability to efficiently learn graph information.
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