Alternatives and similar repositories for NeuBoots:

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

• clovaai / rebias
  Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020
  ☆173Updated 9 months ago
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆39Updated 2 years ago
• swyoon / normalized-autoencoders
  The official repository for <Autoencoding Under Normalization Constraints> (Yoon, Noh and Park, ICML 2021).
  ☆43Updated last year
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆83Updated 3 years ago
• csm9493 / UCL
  The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)
  ☆35Updated 3 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆28Updated 9 months ago
• KaosEngineer / PriorNetworks
  ☆66Updated 5 years ago
• DLR-RM / curvature
  Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.
  ☆30Updated 4 years ago
• rpinsler / active-bayesian-coresets
  ☆40Updated 5 years ago
• daintlab / confidence-aware-learning
  Confidence-Aware Learning for Deep Neural Networks (ICML2020)
  ☆74Updated 4 years ago
• matwilso / maml_numpy
  Implementation of MAML in numpy, deriving gradients and implementing backprop manually
  ☆14Updated 6 years ago
• MOONJOOYOUNG / Deep-learning-Uncertainty-papers
  Uncertainty in Deep Learning Papers
  ☆35Updated 3 years ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆139Updated last year
• jayheo / UA
  ☆24Updated 5 years ago
• JWoong148 / ContinualTrajectoryShifting
  Pytorch implementation of "Large-Scale Meta-Learning with Continual Trajectory Shifting" (ICML 2021)
  ☆17Updated 3 years ago
• xxxnell / spatial-smoothing
  (ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Rob…
  ☆78Updated 2 years ago
• zzzx1224 / A-Bit-More-Bayesian
  Source code of a ICML2021 paper, A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
  ☆12Updated 3 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆39Updated last year
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• SaynaEbrahimi / UCB
  Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020
  ☆74Updated 3 years ago
• SeongokRyu / Bayesian-deep-learning
  Notes and codes of the topic "Bayesian deep learning"
  ☆56Updated 6 years ago
• soochan-lee / CN-DPM
  Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."
  ☆100Updated 4 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆107Updated last year
• LeeDoYup / FixMatch-pytorch
  Unofficial Pytorch code for "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence" in NeurIPS'20. This repo co…
  ☆190Updated 4 years ago
• stanislavfort / exploring_the_limits_of_OOD_detection
  Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanis…
  ☆44Updated 3 years ago
• minkyujeon / MAML_Pytorch
  MAML implementation with pytorch
  ☆11Updated 4 years ago
• ykwon0407 / wdro_local_perturbation
  Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
  ☆21Updated 2 years ago
• bbuing9 / DARP
  Code for the paper "Distribution Aligning Refinery of Pseudo-label for Imbalanced Semi-supervised Learning" (NeurIPS 20)
  ☆73Updated 2 years ago
• alinlab / LfF
  Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)
  ☆91Updated 4 years ago
• dmadras / local-ensembles
  "Detecting Extrapolation with Local Ensembles" by David Madras, James Atwood, and Alex D'Amour
  ☆13Updated 4 years ago