"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
☆209Dec 19, 2019Updated 6 years ago
Alternatives and similar repositories for dl-uncertainty
Users that are interested in dl-uncertainty are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆171Jun 27, 2019Updated 6 years ago
- Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple vers…☆79Jul 13, 2021Updated 4 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Jul 30, 2019Updated 6 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Feb 16, 2018Updated 8 years ago
- Building a Bayesian deep learning classifier☆494Oct 30, 2017Updated 8 years ago
- ☆84Oct 17, 2018Updated 7 years ago
- Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.☆134Jul 4, 2020Updated 5 years ago
- Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf☆30Jan 15, 2020Updated 6 years ago
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆581Feb 26, 2022Updated 4 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,957Oct 20, 2023Updated 2 years ago
- Uncertainty interpretations of the neural network☆32May 3, 2018Updated 7 years ago
- Uncertainty in Medical Image Analysis☆318Nov 6, 2021Updated 4 years ago
- ☆239May 23, 2020Updated 5 years ago
- Uncertainty estimation on Mnist dataset☆23Jan 13, 2018Updated 8 years ago
- This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…☆230Jul 25, 2024Updated last year
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,567Apr 19, 2024Updated last year
- Uncertainty quantification of molecular property prediction using Bayesian deep learning☆45Feb 14, 2019Updated 7 years ago
- Overview of Bayesian Deep Learning☆11Apr 24, 2019Updated 6 years ago
- Pytorch implementation for "Open Compound Domain Adaptation" (CVPR 2020 ORAL)☆142Sep 19, 2021Updated 4 years ago
- Feedforward implementation of Lightweight Probabilistic Deep Networks for Keras and Tensorflow☆14Jul 1, 2019Updated 6 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆253Nov 8, 2018Updated 7 years ago
- ☆42May 14, 2019Updated 6 years ago
- Uncertainty estimation for anchor-based deep object detectors.☆40Nov 24, 2020Updated 5 years ago
- Dropout as Regularization and Bayesian Approximation☆56Nov 17, 2018Updated 7 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Nov 28, 2022Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Apr 8, 2020Updated 5 years ago
- Dropout As A Bayesian Approximation: Code☆204Jul 3, 2015Updated 10 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Apr 12, 2022Updated 3 years ago
- Implementing Bayes by Backprop☆184Mar 25, 2019Updated 6 years ago
- ☆68Dec 20, 2019Updated 6 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,567Feb 2, 2026Updated last month
- Notes and codes of the topic "Bayesian deep learning"☆56Nov 30, 2018Updated 7 years ago
- Unofficial implementation of: Multi-task learning using uncertainty to weigh losses for scene geometry and semantics☆566Nov 1, 2021Updated 4 years ago
- Multi Task Learning Implementation with Homoscedastic Uncertainty in Tensorflow☆54Sep 1, 2018Updated 7 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Jun 7, 2022Updated 3 years ago
- I categorize, annotate and write comments for all research papers I read (550+ papers since 2018).☆409Jan 18, 2026Updated last month
- Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015☆36May 21, 2018Updated 7 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Feb 24, 2016Updated 10 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆62Jun 3, 2018Updated 7 years ago