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In this paper we propose a Bayesian method for estimating architectural parameters of neural networks, namely layer size and network depth.
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Kingma, D. P. and Welling, M. (2013) · 2013
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Mendoza, H., Klein, A., Feurer, M., Springenberg, J. T., and Hutter, F. (2016) · 2016
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Dheeru, D. and Karra Taniskidou, E. (2017) · 2017
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He, K., Zhang, X., Ren, S., and Sun, J. (2016) · 2016
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