Alternatives and similar repositories for bayes-by-backprop

Users that are interested in bayes-by-backprop are comparing it to the libraries listed below

• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆82Updated 11 months ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 3 years ago
• Kyushik / Predictive-Uncertainty-Estimation-using-Deep-Ensemble
  This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
  ☆154Updated 2 years ago
• saxena-mayur / Weight-Uncertainty-in-Neural-Networks
  ☆38Updated 6 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆84Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆76Updated last year
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆70Updated 5 years ago
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆203Updated 3 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆61Updated 7 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆112Updated 2 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆87Updated last year
• nvcuong / variational-continual-learning
  Implementation of the variational continual learning method
  ☆190Updated 6 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆88Updated last year
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆138Updated 7 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• cpark321 / uncertainty-deep-learning
  ☆238Updated 5 years ago
• huyng / incertae
  Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
  ☆68Updated 5 years ago
• izmailovpavel / understandingbdl
  ☆241Updated 2 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆230Updated 3 years ago
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆61Updated 6 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆140Updated 7 years ago