hurrialice / uncertaintiesLinks
AM207 project: dissect aleatoric and epistemic uncertainty
☆90Updated 5 years ago
Alternatives and similar repositories for uncertainties
Users that are interested in uncertainties are comparing it to the libraries listed below
Sorting:
- Implementation of Deep evidential regression paper☆58Updated 4 years ago
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆29Updated 5 years ago
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆168Updated 6 years ago
- ☆110Updated 4 years ago
- ShellingFord221 / My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-VisionPytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple vers…☆79Updated 4 years ago
- using monte carlo dropout to have uncertainty estimation of predictions☆15Updated 5 years ago
- ☆238Updated 5 years ago
- [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".☆43Updated 2 years ago
- Official repository for CVPR21 paper "Deep Stable Learning for Out-Of-Distribution Generalization".☆196Updated 3 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- ☆23Updated 4 years ago
- Knowledge Distillation for Multi-task Learning (ECCV20 Workshops)☆76Updated 2 years ago
- Evidential Deep Learning in PyTorch☆63Updated 2 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆20Updated 3 years ago
- Code for paper Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions.☆47Updated last year
- Latent Discriminant deterministic Uncertainty [ECCV2022]☆42Updated 3 years ago
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆210Updated 5 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- End-to-end Deep Linear Discriminant Analysis in Pytorch.☆17Updated 4 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆104Updated 2 years ago
- MSc group project: Reproduction of 'Multi-Task Learning using Uncertainty to Weigh Losses for Scene Geometry and Semantics'; A. Kendall, …☆91Updated 5 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆144Updated 2 years ago
- The Implementation of "Auto-Lambda: Disentangling Dynamic Task Relationships" [TMLR 2022].☆137Updated 2 years ago
- Discriminative Feature Alignment for Unsupervised Domain Adaptation☆68Updated 4 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 years ago
- ☆42Updated 6 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆27Updated 2 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆114Updated 4 years ago
- PyTorch implementation of the GradNorm☆106Updated last year
- A PyTorch toolkit with 8 popular deep active learning query methods implemented.☆90Updated 4 years ago