atilberk / evidential-deep-learning-to-quantify-classification-uncertainty
Work on Evidential Deep Learning to Quantify Classification Uncertainty
☆55Updated 5 years ago
Related projects: ⓘ
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆51Updated last year
- ☆37Updated 5 years ago
- ☆53Updated 6 years ago
- ☆33Updated 3 years ago
- ☆65Updated 4 years ago
- This repository contains an official implementation of LPBNN.☆39Updated last year
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆55Updated 5 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆73Updated 3 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆41Updated 3 years ago
- Implementation of Deep evidential regression paper☆47Updated 3 years ago
- Generalizing to unseen domains via distribution matching☆69Updated 4 years ago
- ☆81Updated 9 months ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆26Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆73Updated 2 years ago
- ☆38Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated 11 months ago
- Code for experiments to learn uncertainty☆28Updated last year
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆27Updated 4 years ago
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 2 years ago
- Last-layer Laplace approximation code examples☆78Updated 2 years ago
- Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020☆47Updated 3 years ago
- A way to achieve uniform confidence far away from the training data.☆36Updated 3 years ago
- Deep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)☆40Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆109Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).☆98Updated 7 months ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆121Updated last year
- Implementation of Bayesian Gradient Descent☆37Updated 11 months ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆267Updated 2 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆19Updated 2 years ago