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Gradient Regularization as Approximate Variational Inference
We developed Variational Laplace for Bayesian neural networks (BNNs), which exploits a local approximation of the curvature of the likelihood to estimate the ELBO without the need for stochastic sampling of the neural-network weights. The Variational Laplace objective is simple to evaluate, as it is...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8700595/ https://www.ncbi.nlm.nih.gov/pubmed/34945935 http://dx.doi.org/10.3390/e23121629 |