Alternatives and similar repositories for uncertainty-baselines

Users that are interested in uncertainty-baselines are comparing it to the libraries listed below

• AlaaLab / deep-learning-uncertainty
  Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…
  ☆635Updated 3 years ago
• gpleiss / temperature_scaling
  A simple way to calibrate your neural network.
  ☆1,166Updated 5 months ago
• wjmaddox / swa_gaussian
  Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"
  ☆476Updated 2 years ago
• aamini / evidential-deep-learning
  Learn fast, scalable, and calibrated measures of uncertainty using neural networks!
  ☆501Updated 4 years ago
• EFS-OpenSource / calibration-framework
  The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …
  ☆369Updated last year
• JavierAntoran / Bayesian-Neural-Networks
  Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
  ☆1,949Updated 2 years ago
• ENSTA-U2IS-AI / awesome-uncertainty-deeplearning
  This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…
  ☆776Updated 3 weeks ago
• aleximmer / Laplace
  Laplace approximations for Deep Learning.
  ☆529Updated 8 months ago
• google-research / robustness_metrics
  ☆472Updated 2 months ago
• piEsposito / blitz-bayesian-deep-learning
  A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
  ☆978Updated 2 years ago
• ENSTA-U2IS-AI / torch-uncertainty
  Open-source framework for uncertainty and deep learning models in PyTorch
  ☆463Updated 3 weeks ago
• dougbrion / pytorch-classification-uncertainty
  This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"
  ☆504Updated last year
• google / edward2
  A simple probabilistic programming language.
  ☆704Updated 3 months ago
• baal-org / baal
  Bayesian active learning library for research and industrial usecases.
  ☆914Updated 3 weeks ago
• p-lambda / wilds
  A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.
  ☆589Updated last year
• vturrisi / solo-learn
  solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
  ☆1,538Updated 3 weeks ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆275Updated 3 years ago
• yaringal / DropoutUncertaintyExps
  Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"
  ☆576Updated 3 years ago
• facebookresearch / higher
  higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…
  ☆1,627Updated 3 years ago
• Harry24k / bayesian-neural-network-pytorch
  PyTorch implementation of bayesian neural network [torchbnn]
  ☆553Updated last year
• OATML / bdl-benchmarks
  Bayesian Deep Learning Benchmarks
  ☆672Updated 2 years ago
• kumar-shridhar / PyTorch-BayesianCNN
  Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
  ☆1,549Updated last year
• uncertainty-toolbox / uncertainty-toolbox
  Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
  ☆1,961Updated 9 months ago
• f-dangel / backpack
  BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.
  ☆601Updated last month
• google / neural-tangents
  Fast and Easy Infinite Neural Networks in Python
  ☆2,364Updated last year
• awslabs / fortuna
  A Library for Uncertainty Quantification.
  ☆924Updated 8 months ago
• hendrycks / robustness
  Corruption and Perturbation Robustness (ICLR 2019)
  ☆1,120Updated 3 years ago
• cpark321 / uncertainty-deep-learning
  ☆239Updated 5 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆462Updated last year
• hollance / reliability-diagrams
  Reliability diagrams visualize whether a classifier model needs calibration
  ☆163Updated 3 years ago