Revisiting Embeddings for Graph Neural Networks

Image labeling on a network: using social-network metadata for image classification

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Image-based recommendations on styles and substitutes

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Very deep convolutional networks for large-scale image recognition

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Deep residual learning for image recognition

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Inductive Representation Learning on Large Graphs

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Semi-Supervised Classification with Graph Convolutional Networks

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Pitfalls of graph neural network evaluation

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Graph Attention Networks

Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018

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Roberta: A robustly optimized bert pretraining approach

Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019

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Graphsaint: Graph sampling based inductive learning method

Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, and Viktor Prasanna · 2019

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Open graph benchmark: Datasets for machine learning on graphs

Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec · 2020

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How attentive are graph attention networks?

Original

Shaked Brody, Uri Alon, and Eran Yahav · 2021

Later among the works it cites.