bayesian-neural-networks
There are 152 repositories under bayesian-neural-networks topic.
TuringLang/Turing.jl
Bayesian inference with probabilistic programming.
uncertainty-toolbox/uncertainty-toolbox
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
JavierAntoran/Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
janosh/awesome-normalizing-flows
Awesome resources on normalizing flows.
kumar-shridhar/PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
piEsposito/blitz-bayesian-deep-learning
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
IntelLabs/bayesian-torch
A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
kumar-shridhar/Master-Thesis-BayesianCNN
Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
ziatdinovmax/gpax
Gaussian Processes for Experimental Sciences
lightning-uq-box/lightning-uq-box
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
brendanhasz/probflow
A Python package for building Bayesian models with TensorFlow or PyTorch
nitarshan/bayes-by-backprop
PyTorch implementation of "Weight Uncertainty in Neural Networks"
xwinxu/bayeSDE
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
huawei-noah/BGCN
A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).
ykwon0407/UQ_BNN
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
anassinator/bnn
Bayesian Neural Network in PyTorch
j-min/Dropouts
PyTorch Implementations of Dropout Variants
HolyBayes/pytorch_ard
Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks
cambridge-mlg/DUN
Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
Cogito2012/UString
[ACM MM 2020] Uncertainty-based Traffic Accident Anticipation
xxxnell/spatial-smoothing
(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.
ziatdinovmax/NeuroBayes
Fully and Partially Bayesian Neural Nets
pawni/BayesByHypernet
Code for the paper Implicit Weight Uncertainty in Neural Networks
armanihm/GDC
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
pomonam/NoisyNaturalGradient
TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
konstantinos-p/Bayesian-Neural-Networks-Reading-List
A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"
sungyubkim/MCDO
A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
HumBug-Mosquito/HumBugDB
Acoustic mosquito detection code with Bayesian Neural Networks
PlaytikaOSS/pybandits
Python library for Multi-Armed Bandits
kourouklides/artificial_neural_networks
A collection of Methods and Models for various architectures of Artificial Neural Networks
confiwent/BayesMPC
The implementation of "Uncertainty-Aware Robust Adaptive Video Streaming with Bayesian Neural Network and Model Predictive Control" (NOSSDAV 2021)
dtak/ocbnn-public
General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
supernnova/SuperNNova
Open Source Photometric classification https://supernnova.readthedocs.io
dtak/hip-mdp-public
Code for training and testing a Hidden Parameter Markov Decision Process, used to facilitate the transfer of learning
thudzj/ScalableBDL
Code for "BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayeisan Fine-tuning"
gd-zhang/noisy-K-FAC
Natural Gradient, Variational Inference