Alternatives and similar repositories for DDU

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

• KaosEngineer / PriorNetworks
  ☆66Updated 5 years ago
• y0ast / DUE
  Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".
  ☆112Updated 3 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆38Updated 2 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• IntelLabs / AVUC
  Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
  ☆54Updated 2 years ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆160Updated last year
• Jonathan-Pearce / calibration-toolbox
  NumPy library for calibration metrics
  ☆73Updated 6 months ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆87Updated 3 years ago
• JakobCode / UncertaintyInNeuralNetworks_Resources
  ☆109Updated 4 years ago
• hollance / reliability-diagrams
  Reliability diagrams visualize whether a classifier model needs calibration
  ☆155Updated 3 years ago
• dougbrion / pytorch-classification-uncertainty
  This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"
  ☆486Updated last year
• wiseodd / last_layer_laplace
  Last-layer Laplace approximation code examples
  ☆82Updated 3 years ago
• avitase / mder
  Supplementary material to reproduce "Multivariate Deep Evidential Regression"
  ☆20Updated 3 years ago
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated 2 years ago
• MJ10 / DEUP
  Code for experiments to learn uncertainty
  ☆30Updated 2 years ago
• yaohungt / Barlow-Twins-HSIC
  ☆57Updated 3 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆73Updated 3 years ago
• RylanSchaeffer / HarvardAM207-prior-networks
  Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks
  ☆12Updated 5 years ago
• markus93 / NN_calibration
  Calibration of Convolutional Neural Networks
  ☆169Updated 2 years ago
• bethgelab / robustness
  Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.
  ☆137Updated 2 years ago
• daintlab / confidence-aware-learning
  Confidence-Aware Learning for Deep Neural Networks (ICML2020)
  ☆74Updated 5 years ago
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆122Updated 3 years ago
• p3i0t / SimCLR-CIFAR10
  Pytorch SimCLR on CIFAR10 (92.85% test accuracy)
  ☆57Updated 5 years ago
• avihu111 / TypiClust
  Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets
  ☆95Updated 10 months ago
• tayden / ood-metrics
  Metrics for out-of-distribution (OOD) detection performance evaluation
  ☆48Updated 7 months ago
• cure-lab / deep-active-learning
  An implementation of the state-of-the-art Deep Active Learning algorithms
  ☆104Updated last year
• ondrejbohdal / meta-calibration
  Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"
  ☆36Updated 2 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
• zhang64-llnl / Mix-n-Match-Calibration
  ☆38Updated 4 years ago