Alternatives and similar repositories for weight_uncertainty:

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

• team-approx-bayes / dl-with-bayes
  Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
  ☆243Updated 5 years ago
• yaringal / ConcreteDropout
  Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
  ☆248Updated 6 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆140Updated 8 years ago
• ctallec / pyvarinf
  Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch
  ☆359Updated 5 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆265Updated 5 years ago
• alshedivat / keras-gp
  Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.
  ☆249Updated 5 months ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆173Updated 2 years ago
• emtiyaz / vadam
  Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …
  ☆110Updated 6 years ago
• ssydasheng / Bayesian_neural_network_papers
  Papers for Bayesian-NN
  ☆318Updated 5 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆140Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• automl / pybnn
  Bayesian neural network package
  ☆140Updated 3 years ago
• yaringal / BayesianRNN
  Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"
  ☆376Updated 7 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆92Updated 5 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆131Updated 5 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 7 months ago
• yaringal / DropoutUncertaintyCaffeModels
  Dropout As A Bayesian Approximation: Code
  ☆201Updated 9 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆119Updated 5 years ago
• ericmjl / bayesian-deep-learning-demystified
  In which I try to demystify the fundamental concepts behind Bayesian deep learning.
  ☆122Updated 7 years ago
• izmailovpavel / understandingbdl
  ☆235Updated 2 years ago
• paraschopra / bayesian-neural-network-mnist
  Bayesian neural network using Pyro and PyTorch on MNIST dataset
  ☆311Updated 6 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆95Updated 7 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆564Updated 2 years ago
• pyprob / pyprob
  A probabilistic programming system for simulators and high-performance computing (HPC), based on PyTorch
  ☆392Updated 8 months ago
• OATML / bdl-benchmarks
  Bayesian Deep Learning Benchmarks
  ☆666Updated last year
• kyle-dorman / bayesian-neural-network-blogpost
  Building a Bayesian deep learning classifier
  ☆487Updated 7 years ago