解开
发表于 2025-3-26 23:55:13
Background and Traditional Approaches,e will provide a very brief and focused tour of traditional learning approaches over graphs, providing pointers and references to more thorough treatments of these methodological approaches along the way. This background chapter will also serve to introduce key concepts from graph analysis that will form the foundation for later chapters.
CANDY
发表于 2025-3-27 04:05:36
Conclusion, hope is that these chapters provide a sufficient foundation and overview for those who are interested in becoming practitioners of these techniques or those who are seeking to explore new methodological frontiers of this area.
点燃
发表于 2025-3-27 06:28:18
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思想流动
发表于 2025-3-27 10:27:38
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出汗
发表于 2025-3-27 14:36:29
Deep Generative ModelsHowever, a key limitation of those traditional approaches is that they rely on a fixed, hand-crafted generation process. In short, the traditional approaches can generate graphs, but they lack the ability to . a generative model from data.
闪光你我
发表于 2025-3-27 19:15:39
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overhaul
发表于 2025-3-27 22:22:46
Theoretical Motivationsches— which form the basis of most modern GNNs—were proposed by analogy to message passing algorithms for probabilistic inference in graphical models . And lastly, GNNs have been motivated in several works based on their connection to the Weisfeiler-Lehman graph isomorphism test .
仇恨
发表于 2025-3-28 05:32:25
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猛然一拉
发表于 2025-3-28 06:28:18
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ENDOW
发表于 2025-3-28 12:51:31
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