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Permutation-Equivariant Neural Networks
Permutation-Equivariant Neural Networks
PulseAugur coverage of Permutation-Equivariant Neural Networks — every cluster mentioning Permutation-Equivariant Neural Networks across labs, papers, and developer communities, ranked by signal.
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New research unifies GNN expressivity and geometry, explores random features
Two new arXiv papers explore the theoretical underpinnings of Graph Neural Networks (GNNs). The first paper introduces a framework using empirical Rademacher complexity to unify GNN expressivity and geometry, offering t…
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Graph Neural Networks with Random Features Achieve Universality
Researchers have established a new universality result for message-passing graph neural networks (GNNs) that incorporate random node features. This work specifically focuses on Permutation-Equivariant Neural Networks (P…