Alternatives and similar repositories for Predictive-Uncertainty-Estimation-using-Deep-Ensemble

Users that are interested in Predictive-Uncertainty-Estimation-using-Deep-Ensemble are comparing it to the libraries listed below

• cpark321 / uncertainty-deep-learning
  ☆239Updated 5 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆89Updated 5 years ago
• huyng / incertae
  Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
  ☆70Updated 5 years ago
• vvanirudh / deep-ensembles-uncertainty
  My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
  ☆139Updated 7 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆575Updated 3 years ago
• xuwd11 / Dropout_Tutorial_in_PyTorch
  Dropout as Regularization and Bayesian Approximation
  ☆58Updated 6 years ago
• hutec / UncertaintyNN
  Implementation and evaluation of different approaches to get uncertainty in neural networks
  ☆141Updated 7 years ago
• ThirstyScholar / bayes-by-backprop
  " Weight Uncertainty in Neural Networks"
  ☆49Updated 7 years ago
• JakobCode / UncertaintyInNeuralNetworks_Resources
  ☆109Updated 4 years ago
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆204Updated 3 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆112Updated 3 years ago
• cambridge-mlg / DUN
  Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
  ☆77Updated 2 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆71Updated 5 years ago
• AlaaLab / deep-learning-uncertainty
  Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…
  ☆634Updated 3 years ago
• sungyubkim / MCDO
  A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
  ☆57Updated 6 years ago
• wjmaddox / swa_gaussian
  Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
  ☆473Updated 2 years ago
• AnthonyRentsch / calibrated_regression
  A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.
  ☆52Updated 5 years ago
• anassinator / bnn
  Bayesian Neural Network in PyTorch
  ☆91Updated last year
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆45Updated 5 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
• Lingkai-Kong / SDE-Net
  Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates
  ☆116Updated 5 years ago
• kyle-dorman / bayesian-neural-network-blogpost
  Building a Bayesian deep learning classifier
  ☆490Updated 7 years ago
• ykwon0407 / UQ_BNN
  Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
  ☆137Updated 6 years ago
• nvcuong / variational-continual-learning
  Implementation of the variational continual learning method
  ☆195Updated 6 years ago
• probabilistic-learning / HI-VAE
  ☆91Updated 2 years ago
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆76Updated 4 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆233Updated 3 years ago
• biomedia-mira / deepscm
  Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
  ☆288Updated 2 years ago