Alternatives and similar repositories for BayesByHypernet:

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

• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆65Updated 4 years ago
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆30Updated 4 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 8 years ago
• brain-research / ncp
  Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors
  ☆63Updated 4 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• YingzhenLi / Dropout_BBalpha
  Implementations of the ICML 2017 paper (with Yarin Gal)
  ☆38Updated 7 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆32Updated last year
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆53Updated 3 months ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 8 years ago
• ChunyuanLI / pSGLD
  AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)
  ☆35Updated 6 years ago
• CW-Huang / torchkit
  ☆37Updated 5 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, …
  ☆111Updated 6 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• JACKHAHA363 / BBBRNN
  Bayesian Backprop RNN implementation pytorch https://arxiv.org/abs/1704.02798
  ☆25Updated 7 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆140Updated 8 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆39Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• enalisnick / stick-breaking_dgms
  Deep Generative Models with Stick-Breaking Priors
  ☆95Updated 8 years ago
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆26Updated 8 years ago
• da-molchanov / variance-networks
  Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
  ☆39Updated 4 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆75Updated 4 years ago
• abdulfatir / normalizing-flows
  Understanding normalizing flows
  ☆131Updated 5 years ago
• emtiyaz / vmp-for-svae
  Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)
  ☆44Updated 6 years ago
• markvdw / convgp
  Convolutional Gaussian processes based on GPflow.
  ☆96Updated 7 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• MichaelArbel / Scaled-MMD-GAN
  Scaled MMD GAN
  ☆36Updated 5 years ago