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SAILOR: Structural Augmentation Based Tail Node Representation Learning vs Replicate-AI model GFPGAN can help restore old photos
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SAILOR: Structural Augmentation Based Tail Node Representation Learning
In the pursuit of promoting the expressiveness of GNNs for tail nodes, we explore how the deficiency of structural information deteriorates the performance of tail nodes and propose a general Structural Augmentation based taIL nOde Representation learning framework, dubbed as SAILOR, which can jointly learn to augment the graph structure and extract more informative representations for tail nodes.
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Replicate-AI model GFPGAN can help restore old photos
Replicate – Run open-source machine learning models with a cloud API
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