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This study utilizes community structures to address node degree biases in message-passing (MP) via learnable graph augmentations and novel graph transformers.
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Recipe for a general, powerful, scalable graph transformer
Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, and Dominique Beaini · 2022
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Graph representation learning and its applications: A survey
Van Thuy Hoang, Hyeon-Ju Jeon, Eun-Soon You, Yoewon Yoon, Sungyeop Jung, and O-Joun Lee · 2023
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Hub-hub connections matter: Improving edge dropout to relieve over-smoothing in graph neural networks
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Plot structure decomposition in narrative multimedia by analyzing personalities of fictional characters
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