268 citations · 376 across the 6 of their papers we have counts for
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cs.LG2020★ 268 cited
Higher-Order Explanations of Graph Neural Networks via Relevant Walks
Thomas Schnake, Oliver Eberle, Jonas Lederer +4
Graph Neural Networks (GNNs) are a popular approach for predicting graph structured data. As GNNs tightly entangle the input graph into the neural network structure, common explain…
cs.LG2020★ 68 cited
Building and Interpreting Deep Similarity Models
Oliver Eberle, Jochen Büttner, Florian Kräutli +3
Many learning algorithms such as kernel machines, nearest neighbors, clustering, or anomaly detection, are based on the concept of 'distance' or 'similarity'. Before similarities a…