anassinator / bnn

Related projects ⓘ

Alternatives and complementary repositories for bnn

• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆170Updated 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 6 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆68Updated 4 years ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆90Updated 8 months ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆86Updated 4 years ago
• Kyushik / Predictive-Uncertainty-Estimation-using-Deep-Ensemble
  This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble
  ☆148Updated 2 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆134Updated 6 years ago
• ThirstyScholar / bayes-by-backprop
  " Weight Uncertainty in Neural Networks"
  ☆45Updated 6 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆224Updated 2 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆80Updated 4 months ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆127Updated last year
• automl / pybnn
  Bayesian neural network package
  ☆137Updated 3 years ago
• kumar-shridhar / Master-Thesis-BayesianCNN
  Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
  ☆262Updated 5 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆232Updated 3 years ago
• bertini36 / GMM
  Variational Inference in Gaussian Mixture Model
  ☆58Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 4 years ago
• cics-nd / gptorch
  Gaussian processes with PyTorch
  ☆30Updated 3 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆147Updated 5 years ago
• manuwhs / BayesianRNN
  Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.
  ☆40Updated 6 years ago
• Lingkai-Kong / SDE-Net
  Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
  ☆109Updated 4 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 5 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆139Updated 6 years ago
• LCAS / RKN
  ☆47Updated 2 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 2 years ago
• kekeblom / DeepCGP
  Deep convolutional gaussian processes.
  ☆78Updated 5 years ago
• yaringal / HeteroscedasticDropoutUncertainty
  Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.
  ☆139Updated 8 years ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆88Updated 2 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago