Latent Binary Bayesian Neural Networks Using 'torch'

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Documentation for package ‘LBBNN’ version 0.1.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

coef.LBBNN_Net	Get model coefficients (local explanations) of an 'LBBNN_Net' object
Custom_activation	Generate a custom activation function.
FLOW	Class to generate a normalizing flow
Gallstone_Dataset	Gallstone Dataset
get_dataloaders	Wrapper around 'torch::dataloader'
get_local_explanations_gradient	Function to get gradient based local explanations for input-skip LBBNNs.
LBBNN_Conv2d	Class to generate an LBBNN convolutional layer.
LBBNN_Linear	Class to generate an LBBNN feed forward layer
LBBNN_Net	Feed-forward Latent Binary Bayesian Neural Network (LBBNN)
LBBNN_plot	Function to plot an input skip structure after removing weights in non-active paths.
mgp_dataset	Auto MPG daataset
Mice_Dataset	Mice Dataset
plot.LBBNN_Net	Plot 'LBBNN_Net' objects
plot_local_explanations_gradient	Plot the gradient based local explanations for one sample with input-skip LBBNNs.
predict.LBBNN_Net	Obtain predictions from the variational posterior of an 'LBBNN model'
print.LBBNN_Net	Print summary of an 'LBBNN_Net' object
quants	Function to obtain empirical 95% confidence interval, including the mean
Raisin_Dataset	Raisins Dataset
residuals.LBBNN_Net	Residuals from LBBNN fit
RNVP_layer	Single RNVP transform layer.
summary.LBBNN_Net	Summary of LBBNN fit
train_LBBNN	Train an instance of 'LBBNN_Net'.
validate_LBBNN	Validate a trained LBBNN model.