83.4k citations · 107.7k across the 29 of their papers we have counts for
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stat.ML2015★ 440 cited
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma, Tim Salimans, Max Welling
We investigate a local reparameterizaton technique for greatly reducing the variance of stochastic gradients for variational Bayesian inference (SGVB) of a posterior over model par…
cs.LG2015★ 1 cited
Note on Equivalence Between Recurrent Neural Network Time Series Models and Variational Bayesian Models
Jascha Sohl-Dickstein, Diederik P. Kingma
We observe that the standard log likelihood training objective for a Recurrent Neural Network (RNN) model of time series data is equivalent to a variational Bayesian training objec…