nn_alpha_dropout: Alpha-dropout module
In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting
nn_alpha_dropout R Documentation
Alpha-dropout module
Description
An alpha-dropout layer as a torch::nn_module, used in self-normalizing networks.
Usage
nn_alpha_dropout(p = 0.5, inplace = FALSE)
Arguments
p
probability for dropout.
inplace
whether the dropout in performed inplace.
Details
The constructor allows specifying:
- p
probability of an element to be zeroed (default is 0.5),
- inplace
if set to TRUE, will do the operation in-place (default is FALSE).
References
Gunter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter. Self-Normalizing Neural Networks.
Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017.
EQRN documentation built on April 4, 2025, 12:45 a.m.
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| nn_alpha_dropout | R Documentation |
Alpha-dropout module
Description
An alpha-dropout layer as a torch::nn_module, used in self-normalizing networks.
Usage
nn_alpha_dropout(p = 0.5, inplace = FALSE)
Arguments
p |
probability for dropout. |
inplace |
whether the dropout in performed inplace. |
Details
The constructor allows specifying:
- p
probability of an element to be zeroed (default is 0.5),
- inplace
if set to TRUE, will do the operation in-place (default is FALSE).
References
Gunter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter. Self-Normalizing Neural Networks. Advances in Neural Information Processing Systems 30 (NIPS 2017), 2017.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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