vae_loss_independent: A custom loss function for a VAE learning a standard normal...
In converseg/ML2Pvae: Variational Autoencoder Models for IRT Parameter Estimation
Description
Usage
Arguments
Value
View source: R/loss_functions.R
Description
A custom loss function for a VAE learning a standard normal distribution
Usage
1
vae_loss_independent(encoder, kl_weight, rec_dim)
Arguments
encoder
the encoder model of the VAE, used to obtain z_mean and z_log_var from inputs
kl_weight
weight for the KL divergence term
rec_dim
the number of nodes in the input/output of the VAE
Value
returns a function whose parameters match keras loss format
converseg/ML2Pvae documentation built on April 6, 2021, 1:46 a.m.
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Description Usage Arguments Value
View source: R/loss_functions.R
Description
A custom loss function for a VAE learning a standard normal distribution
Usage
1 | vae_loss_independent(encoder, kl_weight, rec_dim)
|
Arguments
encoder |
the encoder model of the VAE, used to obtain z_mean and z_log_var from inputs |
kl_weight |
weight for the KL divergence term |
rec_dim |
the number of nodes in the input/output of the VAE |
Value
returns a function whose parameters match keras loss format
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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