Methods › General › Attention Modules › Hopfield Layer
Hopfield Layer
Introduced by Hubert Ramsauer et al. in Hopfield Networks is All You Need
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Hopfield Layer is a module that enables a network to associate two sets of vectors. This general functionality allows for transformer-like self-attention, for decoder-encoder attention, for time series prediction (maybe with positional encoding), for sequence analysis, for multiple instance learning, for learning with point sets, for combining data sources by associations, for constructing a memory, for averaging and pooling operations, and for many more.
In particular, the Hopfield layer can readily be used as plug-in replacement for existing layers like pooling layers (max-pooling or average pooling, permutation equivariant layers, GRU & LSTM layers, and attention layers. The Hopfield layer is based on modern Hopfield networks with continuous states that have very high storage capacity and converge after one update.
Papers archive 2025-07-28
3 shown of 3, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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HBert + BiasCorp -- Fighting Racism on the Web 6 Apr 2021 · 0 repositories · arXiv:2104.02242
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HiCOMEX: Facial Action Unit Recognition Based on Hierarchy Intensity Distribution and COMEX Relation Learning 23 Sep 2020 · 0 repositories · arXiv:2009.10892
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Hopfield Networks is All You Need 16 Jul 2020 · 3 repositories · arXiv:2008.02217Syntology ran 0 of 9 samples · 9 unverified
Tasks archive 2025-07-28
9 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Action Unit Detection | 1 |
| All | 1 |
| Drug Design | 1 |
| Facial Action Unit Detection | 1 |
| Immune Repertoire Classification | 1 |
| Multiple Instance Learning | 1 |
| Relation | 1 |
| Representation Learning | 1 |
| Retrieval | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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