Abstract: Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertainty of ...
Abstract: The non-Euclidean nature of graphs made them inaccessible to standard deep learning techniques that rely on fixed-size, ordered inputs. Graph Neural Networks (GNNs) are essential for serving ...
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