DropConnect is effective in modeling uncertainty of Bayesian deep networks
Abstract Deep neural networks (DNNs) have achieved state-of-the-art performance in many important domains, including medical diagnosis, security, and autonomous driving. In domains where safety is highly critical, an erroneous decision can result in serious consequences. While a perfect prediction a...
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| Auteurs principaux: | , , , , , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/ff6a04b4a5f649c98b73aae38d3ec8c3 |
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