ykwon0407 / UQ_BNN
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
☆136Updated 5 years ago
Alternatives and similar repositories for UQ_BNN:
Users that are interested in UQ_BNN are comparing it to the libraries listed below
- ☆84Updated 6 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆140Updated 6 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☆30Updated 5 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆152Updated 2 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆136Updated 7 years ago
- Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)☆85Updated this week
- This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.☆16Updated last year
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆210Updated 5 years ago
- Stochastic Segmentation Networks☆66Updated 4 years ago
- ☆24Updated 5 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆248Updated 6 years ago
- ☆228Updated 4 years ago
- Code for the ICCV 2019 paper "Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation"☆94Updated last year
- Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.☆132Updated 4 years ago
- Uncertainty in Medical Image Analysis☆317Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆271Updated 2 years ago
- Tensorflow Code for "PHiSeg: Capturing Uncertainty in Medical Image Segmentation", Proc. MICCAI 2019☆123Updated 2 years ago
- Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands☆106Updated 4 years ago
- Migrate to PyTorch. Re-implementation of Bayesian Convolutional Neural Networks (BCNNs)☆59Updated 4 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆58Updated 6 years ago
- Code for "Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference" (NeurIPS Bayesian Deep Learning W…☆23Updated 4 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 years ago
- Dropout as Regularization and Bayesian Approximation☆57Updated 6 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆62Updated 4 years ago
- 3D Bayesian Convolutional Neural Network (BCNN) for Credible Geometric Uncertainty. Code for the paper: https://arxiv.org/abs/1910.10793☆62Updated last year
- A PyTorch implementation of the Probabilistic U-Net, applied to probabilistic glioma growth☆43Updated 5 years ago
- A Probabilistic U-Net for segmentation of ambiguous images implemented in PyTorch☆277Updated 6 years ago
- ☆32Updated 7 years ago
- ☆66Updated 5 years ago