Alternatives and similar repositories for bayesian_neural_networks_demo

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

• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 5 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆110Updated 3 years ago
• TyXe-BDL / TyXe
  ☆152Updated 3 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆196Updated 2 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆121Updated 5 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆58Updated 4 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆47Updated 3 years ago
• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆175Updated 3 months ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆124Updated 8 months ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 5 years ago
• dfm / gp
  A tutorial about Gaussian process regression
  ☆189Updated 5 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• kamdh / tvart
  Time-varying Autoregression with Low Rank Tensors
  ☆15Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 5 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆264Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆45Updated 5 years ago
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 5 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 2 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆67Updated 7 months ago
• yuqirose / tensor_train_RNN
  Clean repo for tensor-train RNN implemented in TensorFlow
  ☆69Updated 6 years ago