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bayesian-neural-networks
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99 public repositories
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Bayesian inference with probabilistic programming.
Updated
Apr 14, 2022
Julia
A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
Updated
Apr 13, 2022
Python
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
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Feb 5, 2021
Python
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
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Apr 15, 2022
Python
Awesome resources on normalizing flows.
Updated
Apr 4, 2022
Python
Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
PyTorch implementation of "Weight Uncertainty in Neural Networks"
Updated
Apr 12, 2022
Jupyter Notebook
A Python package for building Bayesian models with TensorFlow or PyTorch
Updated
Jul 14, 2021
Python
A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
Updated
Sep 8, 2019
Python
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
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Mar 3, 2022
Python
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
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Jul 30, 2019
Jupyter Notebook
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
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Feb 11, 2022
Python
PyTorch Implementations of Dropout Variants
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Jan 7, 2018
Jupyter Notebook
Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
Updated
Nov 29, 2021
Python
Code for the paper Implicit Weight Uncertainty in Neural Networks
Updated
Nov 14, 2019
Jupyter Notebook
Updated
Mar 12, 2022
Jupyter Notebook
TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC"
Updated
Jan 12, 2019
Python
Bayesian Neural Network in PyTorch
Updated
Sep 14, 2019
Python
A collection of Methods and Models for various architectures of Artificial Neural Networks
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Feb 10, 2022
Python
General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
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Mar 26, 2021
Python
Natural Gradient, Variational Inference
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Jan 13, 2020
Python
[ACM MM 2020] Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning.
Updated
Jan 21, 2022
Python
Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.
Updated
Feb 16, 2018
Jupyter Notebook
A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
Updated
Jan 1, 2019
Jupyter Notebook
Acoustic mosquito detection code with Bayesian Neural Networks
Updated
Oct 4, 2021
Jupyter Notebook
(Preprint) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.
Updated
Dec 12, 2021
Python
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
Updated
Aug 13, 2020
Python
Code for training and testing a Hidden Parameter Markov Decision Process, used to facilitate the transfer of learning
Updated
Dec 28, 2017
Python
Python 3.7 version of David Barber's MATLAB BRMLtoolbox
Updated
Aug 18, 2018
Python
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Hi @JavierAntoran @stratisMarkou,
First of all, thanks for making all of this code available - it's been great to look through!
Im currently spending some time trying to work through the Weight Uncertainty in Neural Networks in order to implement Bayes-by-Backprop. I was struggling to understand the difference between your implementation of `Bayes-by-Bac