375 citations · 537 across the 4 of their papers we have counts for
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cs.LG2020★ 375 cited
Scaling Graph Neural Networks with Approximate PageRank
Aleksandar Bojchevski, Johannes Gasteiger, Bryan Perozzi +5
Graph neural networks (GNNs) have emerged as a powerful approach for solving many network mining tasks. However, learning on large graphs remains a challenge - many recently propos…
cs.LG2018★ 162 cited
Adversarial Attacks on Node Embeddings via Graph Poisoning
Aleksandar Bojchevski, Stephan Günnemann
The goal of network representation learning is to learn low-dimensional node embeddings that capture the graph structure and are useful for solving downstream tasks. However, despi…