Alternatives and similar repositories for Bayesian_CNN:

Users that are interested in Bayesian_CNN are comparing it to the libraries listed below

• raj-shah / BayesianCNN
  Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015
  ☆36Updated 6 years ago
• alexrakowski / mc-dropout-mnist
  Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf
  ☆30Updated 5 years ago
• kenya-sk / mc_dropout_tensorflow
  This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.
  ☆16Updated last year
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 5 years ago
• Riashat / Deep-Bayesian-Active-Learning
  Code for Deep Bayesian Active Learning (ICML 2017)
  ☆112Updated 6 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆140Updated 6 years ago
• Riashat / Active-Learning-Bayesian-Convolutional-Neural-Networks
  Active Learning on Image Data using Bayesian ConvNets
  ☆137Updated 8 years ago
• ykwon0407 / UQ_BNN
  Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
  ☆136Updated 5 years ago
• ThirstyScholar / bayes-by-backprop
  " Weight Uncertainty in Neural Networks"
  ☆45Updated 6 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆173Updated 2 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆318Updated 5 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆135Updated 7 years ago
• Kyushik / Predictive-Uncertainty-Estimation-using-Deep-Ensemble
  This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
  ☆152Updated 2 years ago
• maka89 / Deep-Kernel-GP
  Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood
  ☆94Updated 7 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆83Updated 8 months ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 5 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆565Updated 2 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆51Updated 4 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆232Updated 3 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated 11 months ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆201Updated 9 years ago
• Era-Dorta / tf_mvg
  Multivariate Gaussian distributions for Tensorflow.
  ☆23Updated 5 years ago
• cpark321 / uncertainty-deep-learning
  ☆228Updated 4 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 5 years ago
• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆244Updated 5 years ago
• wzell / mann
  Unsupervised Domain Adaptation with Moment Alignment Neural Networks (Keras)
  ☆60Updated last year
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• RobRomijnders / bayes_nn
  Uncertainty interpretations of the neural network
  ☆32Updated 6 years ago