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...
| Hlavní autoři: | , |
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| Médium: | Článek |
| Jazyk: | English |
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MDPI AG
2021-12-01
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| Edice: | Entropy |
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| On-line přístup: | https://www.mdpi.com/1099-4300/23/12/1629 |