# guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network

<https://repo.masters-masters.com/repos/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network>

[Accueil](https://repo.masters-masters.com/) › [guillaume-chevalier](https://repo.masters-masters.com/owners/guillaume-chevalier) › [Linear-Attention-Recurrent-Neural-Network](https://repo.masters-masters.com/repos/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network)

guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network, dépôt open source à 148 étoiles sur GitHub. Carte Prototype de RepoMasters.

| Champ | Valeur |
| --- | --- |
| Propriétaire | [guillaume-chevalier](https://repo.masters-masters.com/owners/guillaume-chevalier) |
| Étoiles | 148 |
| Forks | 32 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | MIT |
| Création | 2018 |
| Sujets | rnn, lstm, attention-mechanism, attention-model, attention-is-all-you-need, recurrent-neural-networks, pytorch |
| Rang | [Prototype (100 à 249 ★)](https://repo.masters-masters.com/ranks/rush) |
| Voir sur GitHub | [guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network](https://github.com/guillaume-chevalier/Linear-Attention-Recurrent-Neural-Network) |

## Fiche du dépôt

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, ju…

Rang des dépôts qui ont 100 à 249 ★ sur GitHub. Probabilité publiée par carte tirée : 70 %. Rareté : Commune.

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