Gradient Regularization as Approximate Variational Inference
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DOI: 10.3390/e23121629
Abstract: 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… read more here.
Keywords: regularization approximate; approximate variational; gradient regularization; variational inference ... See more keywords