#Bayesian-neural-networks
Showing 12 of 12 repositories tagged #bayesian-neural-networks, ranked by stars
Bayesian inference with probabilistic programming.
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Awesome resources on normalizing flows.
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
A Python package for building Bayesian models with TensorFlow or PyTorch
Bayesian Neural Network in PyTorch
Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
A collection of Methods and Models for various architectures of Artificial Neural Networks
Open Source Photometric classification https://supernnova.readthedocs.io