atilberk / evidential-deep-learning-to-quantify-classification-uncertaintyLinks
Work on Evidential Deep Learning to Quantify Classification Uncertainty
☆60Updated 6 years ago
Alternatives and similar repositories for evidential-deep-learning-to-quantify-classification-uncertainty
Users that are interested in evidential-deep-learning-to-quantify-classification-uncertainty are comparing it to the libraries listed below
Sorting:
- ☆42Updated 6 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- ☆66Updated 5 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 years ago
- ☆37Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆142Updated 2 years ago
- Generalizing to unseen domains via distribution matching☆72Updated 4 years ago
- ☆53Updated 7 years ago
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆36Updated last year
- Last-layer Laplace approximation code examples☆82Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆77Updated 3 years ago
- Addressing Failure Prediction by Learning Model Confidence☆173Updated 2 years ago
- ☆24Updated 3 years ago
- This repository contains an official implementation of LPBNN.☆38Updated 2 years ago
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- Calibration of Convolutional Neural Networks☆166Updated 2 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
- Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).☆101Updated last month
- Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020☆50Updated 4 years ago
- SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]☆137Updated 4 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning☆31Updated 2 years ago
- ☆46Updated 4 years ago
- The implementation code for Uncertainty-based Continual Learning with Adaptive Regularization (Neurips 2019)☆35Updated 4 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆31Updated 3 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆69Updated 4 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago