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Watch Your Step - Learning Node Embeddings via Graph Attention.

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018): 9198-9208

Cited by: 134|Views117
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Abstract

Graph embedding methods represent nodes in a continuous vector space, preserving different types of relational information from the graph. There are many hyperparameters to these methods (e.g. the length of a random walk) which have to be manually tuned for every graph. In this paper, we replace previously fixed hyperparameters with train...More

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