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Found 2 papers, 1 papers with code
Fast Adaptive Weight Noise
Marginalising out uncertain quantities within the internal representations or parameters of neural networks is of central importance for a wide range of learning techniques, such as empirical, variational or full Bayesian methods.
On Fast Dropout and its Applicability to Recurrent Networks
Recurrent Neural Networks (RNNs) are rich models for the processing of sequential data.
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