Learning Deep Generative Models of Graphs

ICLR 2018 Yujia LiOriol VinyalsChris DyerRazvan PascanuPeter Battaglia

Graphs are fundamental data structures which concisely capture the relational structure in many important real-world domains, such as knowledge graphs, physical and social interactions, language, and chemistry. Here we introduce a powerful new approach for learning generative models over graphs, which can capture both their structure and attributes... (read more)

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