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Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics
Recurrent neural networks (RNNs) are a widely used tool for modeling sequential data, yet they are often treated as inscrutable black boxes. Given a trained recurrent network, we would like to reverse engineer it–to obtain a quantitative, interpretable description of how it solves a particular task....
Gorde:
| Argitaratua izan da: | Adv Neural Inf Process Syst |
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| Egile Nagusiak: | , , , , |
| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
2019
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7416638/ https://ncbi.nlm.nih.gov/pubmed/32782423 |
| Etiketak: |
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