221 citations · 1.1k across the 24 of their papers we have counts for
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cs.LG2020★ 15 cited
Single-Node Attacks for Fooling Graph Neural Networks
Ben Finkelshtein, Chaim Baskin, Evgenii Zheltonozhskii +1
Graph neural networks (GNNs) have shown broad applicability in a variety of domains. These domains, e.g., social networks and product recommendations, are fertile ground for malici…
cs.LG2020★ 89 cited
On the Bottleneck of Graph Neural Networks and its Practical Implications
Uri Alon, Eran Yahav
Since the proposal of the graph neural network (GNN) by Gori et al. (2005) and Scarselli et al. (2008), one of the major problems in training GNNs was their struggle to propagate i…
cs.PL2020
A Structural Model for Contextual Code Changes
Shaked Brody, Uri Alon, Eran Yahav
We address the problem of predicting edit completions based on a learned model that was trained on past edits. Given a code snippet that is partially edited, our goal is to predict…