199 citations · 474 across the 27 of their papers we have counts for
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stat.ML2014★ 199 cited
Learning Stochastic Recurrent Networks
Justin Bayer, Christian Osendorfer
Leveraging advances in variational inference, we propose to enhance recurrent neural networks with latent variables, resulting in Stochastic Recurrent Networks (STORNs). The model…
stat.ML2014★ 2 cited
Regularizing Recurrent Networks - On Injected Noise and Norm-based Methods
Saahil Ognawala, Justin Bayer
Advancements in parallel processing have lead to a surge in multilayer perceptrons' (MLP) applications and deep learning in the past decades. Recurrent Neural Networks (RNNs) give…
stat.ML2014★ 2 cited
Variational inference of latent state sequences using Recurrent Networks
Justin Bayer, Christian Osendorfer
Recent advances in the estimation of deep directed graphical models and recurrent networks let us contribute to the removal of a blind spot in the area of probabilistc modelling of…