Methods › Sequential › Recurrent Neural Networks › Associative LSTM

Associative LSTM

1 paper tagged archive 2025-07-28

Introduced by Ivo Danihelka et al. in Associative Long Short-Term Memory

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

An Associative LSTM combines an LSTM with ideas from Holographic Reduced Representations (HRRs) to enable key-value storage of data. HRRs use a “binding” operator to implement key-value binding between two vectors (the key and its associated content). They natively implement associative arrays; as a byproduct, they can also easily implement stacks, queues, or lists.

PaperSource

Papers archive 2025-07-28

1 shown of 1, 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.

Tasks archive 2025-07-28

2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Memorization1
Retrieval1

Usage over time archive 2025-07-28

Papers per year tagged with Associative LSTM: 2016 to 2016, peak 1 1 0 2016: 1 paper 2016
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

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

Recurrent Neural Networks

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