ykwon0407 / UQ_BNNView external linksLinks
Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)
☆137Jul 30, 2019Updated 6 years ago
Alternatives and similar repositories for UQ_BNN
Users that are interested in UQ_BNN are comparing it to the libraries listed below
Sorting:
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆209Dec 19, 2019Updated 6 years ago
- Uncertainty in Medical Image Analysis☆318Nov 6, 2021Updated 4 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
- Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation☆56Oct 3, 2023Updated 2 years ago
- Implementation and evaluation of different approaches to get uncertainty in neural networks☆141Feb 16, 2018Updated 7 years ago
- Tensorflow Code for "PHiSeg: Capturing Uncertainty in Medical Image Segmentation", Proc. MICCAI 2019☆129Nov 22, 2022Updated 3 years ago
- Building a Bayesian deep learning classifier☆493Oct 30, 2017Updated 8 years ago
- Uncertainty-Guided Interactive Refinement for Segmentation☆57May 21, 2021Updated 4 years ago
- This is official Pytorch implementation of "Uncertainty quantification in medical image segmentation with Normalizing Flows", Raghavendra…☆30Oct 23, 2022Updated 3 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆62Jun 3, 2018Updated 7 years ago
- ☆24Mar 31, 2021Updated 4 years ago
- Classification uncertainty using Bayesian neural networks☆33Jun 28, 2016Updated 9 years ago
- Models and Codes for the paper Question Relevance in VQA: Identifying Non-Visual And False-Premise Questions☆14Aug 6, 2018Updated 7 years ago
- Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832☆253Nov 8, 2018Updated 7 years ago
- Code release for "GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions", ICCV 2019☆13Nov 21, 2022Updated 3 years ago
- Uncertainty estimation on Mnist dataset☆23Jan 13, 2018Updated 8 years ago
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆170Jun 27, 2019Updated 6 years ago
- ☆19Feb 6, 2019Updated 7 years ago
- A PyTorch implementation of the Probabilistic U-Net, applied to probabilistic glioma growth☆43Jul 10, 2019Updated 6 years ago
- Code and models for our paper "Risk-Aware Machine Learning Classifier for Skin Lesion Diagnosis"☆10Aug 2, 2024Updated last year
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆581Feb 26, 2022Updated 3 years ago
- An Implementation of "Small steps and giant leaps: Minimal Newton solvers for Deep Learning" In pytorch☆21Jul 16, 2018Updated 7 years ago
- Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015☆36May 21, 2018Updated 7 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 Deep Learning Benchmarks☆671Mar 24, 2023Updated 2 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,562Apr 19, 2024Updated last year
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019☆14Apr 25, 2019Updated 6 years ago
- Domain Agnostic Normalization layer for Unsupervised Domain Adaptation☆11Dec 8, 2022Updated 3 years ago
- A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.☆562Mar 24, 2023Updated 2 years ago
- Python wrapper around DEEDS - efficient algorithm for 3D discrete deformable image registration, reaching the highest accuracy in several…☆16Jul 1, 2022Updated 3 years ago
- ☆17Jun 20, 2024Updated last year
- Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.☆133Jul 4, 2020Updated 5 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
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Apr 8, 2020Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Dec 15, 2017Updated 8 years ago
- Code for our MIDL2020 submission "Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning".☆31Apr 27, 2021Updated 4 years ago
- Python package for evaluating model calibration in classification☆20Nov 12, 2019Updated 6 years ago
- Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network☆61Jun 25, 2019Updated 6 years ago
- [ECCV 2018] Sparsely Aggreagated Convolutional Networks https://arxiv.org/abs/1801.05895☆124Oct 10, 2018Updated 7 years ago