Alternatives and similar repositories for Bayesian_CNN

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

• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• raj-shah / BayesianCNN
  Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015
  ☆36Updated 7 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
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆141Updated 7 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆139Updated 7 years ago
• ykwon0407 / UQ_BNN
  Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
  ☆137Updated 6 years ago
• Riashat / Active-Learning-Bayesian-Convolutional-Neural-Networks
  Active Learning on Image Data using Bayesian ConvNets
  ☆138Updated 8 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆325Updated 6 years ago
• kyle-dorman / bayesian-neural-network-blogpost
  Building a Bayesian deep learning classifier
  ☆490Updated 7 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆575Updated 3 years ago
• paraschopra / bayesian-neural-network-mnist
  Bayesian neural network using Pyro and PyTorch on MNIST dataset
  ☆315Updated 6 years ago
• chaitanya100100 / VAE-for-Image-Generation
  Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR1…
  ☆123Updated 7 years ago
• mcgrady20150318 / BayesianNeuralNetwork
  a repo sharing Bayesian Neural Network recent papers
  ☆216Updated 6 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆91Updated last year
• Kyushik / Predictive-Uncertainty-Estimation-using-Deep-Ensemble
  This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
  ☆157Updated 3 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• Riashat / Deep-Bayesian-Active-Learning
  Code for Deep Bayesian Active Learning (ICML 2017)
  ☆112Updated 7 years ago
• yaringal / ConcreteDropout
  Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
  ☆254Updated 6 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
• wmingwei / restricted-boltzmann-machine-deep-belief-network-deep-boltzmann-machine-in-pytorch
  ☆52Updated 8 years ago
• manuwhs / BayesianRNN
  Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.
  ☆40Updated 7 years ago
• axelbrando / Mixture-Density-Networks-for-distribution-and-uncertainty-estimation
  A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
  ☆355Updated 8 years ago
• RobRomijnders / weight_uncertainty
  Implementing Bayes by Backprop
  ☆184Updated 6 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 7 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆361Updated 6 years ago
• tabacof / bayesian-nn-uncertainty
  Classification uncertainty using Bayesian neural networks
  ☆33Updated 9 years ago
• cpark321 / uncertainty-deep-learning
  ☆239Updated 5 years ago
• felix-laumann / Bayesian_CNN_ContinualLearning
  Interpreting Bayesian inference as continual learning with a CNN
  ☆22Updated 7 years ago