bayesian-torch
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IntelLabs
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
https://github.com/IntelLabs/bayesian-torch/blob/f6f516e9b3721466aa0036c735475a421cc3ce80/bayesian_torch/layers/variational_layers/conv_variational.py#L784-L786  When I try to convert a deterministic autoencoder into a bayesian one with a ConvTranspose2d layer I get the error "Exception has occurred: TypeError conv_transpose2d(): argument 'groups' (position...
@peteriz @jpablomch @ranganathkrishnan we can get the $\mu$ and $\sigma$ of each weight ,so how it can be used to quantization which mapping the $w_{float32 }$ into $w_{int8}$
Hi, i am rather new to the concept of BNNs and wondering if there is a reason for the BatchNorm affine transformation parameters not being considered as random variables, i.e....
Is it possible to let the net give back a variance or standard deviation with the prediction (when using the bayesian network for regression) to calculate a confidence interval? Or...
Hello, I am trying to use this repository for regression tasks (I can see the examples seem to focus on classification tasks). I would like to do estimate epistemic and...
Added function for calculating skew-geometric jensen shannon divergence instead of kl-divergence with minimal code changes
I just wanted to make a small improvement to the readme to increase legibility.
There is a mean taken inside [BaseVariationalLayer_.kl_div()](https://github.com/IntelLabs/bayesian-torch/blob/main/bayesian_torch/layers/base_variational_layer.py). But later a sum is used inside [get_kl_loss()](https://github.com/IntelLabs/bayesian-torch/blob/main/bayesian_torch/models/dnn_to_bnn.py) & when reducing the KL loss of a layer's bias & weights (e.g. inside [Conv2dReparameterization.kl_loss()](https://github.com/IntelLabs/bayesian-torch/blob/main/bayesian_torch/layers/variational_layers/conv_variational.py))....
Hi, I'm working on uncertainty prediction using Bayesian Neural Networks (BNNs). I trained a BNN on a dataset where all values were positive. The training went well, and the model...
Thank you for providing a powerful Bayesian-torch library! I am currently learning about this and now I have a problem. I want to fit a distribution using a variational Bayesian...
