Deep Sets¶
Zaheer, M., Kottur, S., Ravanbakhsh, S., Poczos, B., Salakhutdinov, R., & Smola, A. J. (2017). Deep Sets. Advances in Neural Information Processing Systems.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Permutation Equivariance Audit
- The formal target is the design principle behind set- and graph-learning: a function over a collection is well-posed only if it is permutation-invariant or permutation-equivariant as appropriate
This sourceFormalizes that functions on sets must be invariant to element order and derives conditions for permutation-equivariant deep layers when outputs should transform with the input permutation.
- The formal target is the design principle behind set- and graph-learning: a function over a collection is well-posed only if it is permutation-invariant or permutation-equivariant as appropriate
Verification¶
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Registry ID ref:afc1430cf202 · see in the full table