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View Code? Open in Web Editor NEWImplementation of "Bayesian Learning of Neural Network Architectures"
Home Page: http://proceedings.mlr.press/v89/dikov19a/dikov19a.pdf
License: MIT License
Implementation of "Bayesian Learning of Neural Network Architectures"
Home Page: http://proceedings.mlr.press/v89/dikov19a/dikov19a.pdf
License: MIT License
I've read your paper "Bayesian learning of neural network architectures". Thank you for sharing the code. I want to follow your paper.
I'm confused with the sentence "Also, given that the prior distribution p(W) is a Gaussian, the KL-divergence term for the network weights will be computed analytically and thus will reduce the variance in the gradient estimates." in the last paragraph of Section 2.1.
What is the meaning of "be computed analytically"?
I don't know how the KL-divergence term for the network weights KL(qη(W) || p(W)) is calculated practically.
And I also can not find the corresponding code in GitHub. It seems to be omitted. And why?
Can you help me?
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