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20202024
most citedGraph Neural Networks for Learning Equivariant Representations of Neural Networks

3 citations · 10 across the 11 of their papers we have counts for

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2 papers · 1 filter

cs.LG2021★ 2 cited

Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation

Yan Zhang, David W. Zhang, Simon Lacoste-Julien +2

Most set prediction models in deep learning use set-equivariant operations, but they actually operate on multisets. We show that set-equivariant functions cannot represent certain…

cs.LG2021

Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets

David W. Zhang, Gertjan J. Burghouts, Cees G. M. Snoek

This paper aims for set-to-hypergraph prediction, where the goal is to infer the set of relations for a given set of entities. This is a common abstraction for applications in part…