Set transformer: A framework for attention-based permutation-invariant neural networks
Many machine learning tasks such as multiple instance learning, 3D shape recognition, and few-shot image classification are defined on sets of instances. Since solutions to such problems do not depend on the order of elements of the set, models used to address them should be permutation invariant. W...
| Main Authors: | , , , , , |
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| Format: | Conference item |
| Published: |
PMLR
2019
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