Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
☆275Mar 17, 2022Updated 3 years ago
Alternatives and similar repositories for deterministic-uncertainty-quantification
Users that are interested in deterministic-uncertainty-quantification are comparing it to the libraries listed below
Sorting:
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆147Jun 2, 2023Updated 2 years ago
- Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertaint…☆640Aug 1, 2022Updated 3 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,567Feb 2, 2026Updated last month
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Jun 7, 2022Updated 3 years ago
- This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…☆52Jul 25, 2021Updated 4 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆513Jan 2, 2024Updated 2 years ago
- Last-layer Laplace approximation code examples☆83Oct 18, 2021Updated 4 years ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆478Jul 6, 2023Updated 2 years ago
- Latent Discriminant deterministic Uncertainty [ECCV2022]☆43Jul 25, 2022Updated 3 years ago
- Code for experiments to learn uncertainty☆30Mar 16, 2023Updated 2 years ago
- ☆252Dec 27, 2022Updated 3 years ago
- Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …☆87Apr 5, 2023Updated 2 years ago
- Official repository for the paper "Fast Predictive Uncertainty for Classification with Bayesian Deep Networks". Accepted at UAI 2022. htt…☆12May 25, 2022Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Jun 17, 2024Updated last year
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆581Feb 26, 2022Updated 4 years ago
- Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks☆12Dec 22, 2019Updated 6 years ago
- Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization☆1,977Mar 5, 2025Updated 11 months ago
- ☆110Jun 29, 2021Updated 4 years ago
- ☆239May 23, 2020Updated 5 years ago
- ☆42May 14, 2019Updated 6 years ago
- Bayesian Deep Learning Benchmarks☆672Mar 24, 2023Updated 2 years ago
- Learning error bars for neural network predictions☆72Jan 9, 2020Updated 6 years ago
- ☆68Dec 20, 2019Updated 6 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Jan 8, 2019Updated 7 years ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆786Dec 5, 2025Updated 2 months ago
- (ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks☆50Dec 14, 2022Updated 3 years ago
- ☆472Feb 2, 2026Updated last month
- ☆428Aug 28, 2021Updated 4 years ago
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆170Jun 27, 2019Updated 6 years ago
- Laplace approximations for Deep Learning.☆535Apr 22, 2025Updated 10 months ago
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆22Nov 28, 2022Updated 3 years ago
- Belief matching framework official implementation☆41Mar 24, 2023Updated 2 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,565Apr 19, 2024Updated last year
- Multidimensional Uncertainty-Aware Evidential Neural Networks ( AAAI2021)☆16Aug 19, 2021Updated 4 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆21Feb 25, 2022Updated 4 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Aug 3, 2022Updated 3 years ago
- A simple way to calibrate your neural network.☆1,169Jul 26, 2025Updated 7 months ago
- Bayesian Deep Learning: A Survey☆520Oct 10, 2025Updated 4 months ago
- Repository for the ICML 2021 paper: https://arxiv.org/abs/2103.04886☆13Jan 24, 2022Updated 4 years ago