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Learning Numerosity Representations with Transformers: Number Generation Tasks and Out-of-Distribution Generalization
One of the most rapidly advancing areas of deep learning research aims at creating models that learn to disentangle the latent factors of variation from a data distribution. However, modeling joint probability mass functions is usually prohibitive, which motivates the use of conditional models assum...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8303966/ https://ncbi.nlm.nih.gov/pubmed/34356398 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23070857 |
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