yizhanyang / Uncertainty-Estimation-BNN
Epistemic Uncertainty Estimation with Monte Carlo Dropout
☆8Updated 5 years ago
Alternatives and similar repositories for Uncertainty-Estimation-BNN:
Users that are interested in Uncertainty-Estimation-BNN are comparing it to the libraries listed below
- 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
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆136Updated 5 years ago
- Code for "Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference" (NeurIPS Bayesian Deep Learning W…☆24Updated 5 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- Semi-supervised variational autoencoder for survival prediction☆14Updated last year
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆101Updated 5 years ago
- Code for our MIDL2020 submission "Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning".☆31Updated 3 years ago
- Uncertainty estimation on Mnist dataset☆23Updated 7 years ago
- Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition☆63Updated 3 years ago
- Measuring uncertainty in Deep Learning for Medical Imaging using Monte Carlo Dropout☆13Updated 6 years ago
- ☆34Updated 4 years ago
- Code for the paper "Curriculum Dropout", ICCV 2017☆25Updated 6 years ago
- Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"☆51Updated 3 years ago
- ☆40Updated 5 years ago
- Experiments on meta-learning algorithms to solve few-shot domain adaptation☆10Updated 3 years ago
- Learns effective selective labeling strategies for medical images using deep reinforcement learning and meta learning☆26Updated 3 years ago
- using monte carlo dropout to have uncertainty estimation of predictions☆14Updated 5 years ago
- t-sne visualization of mnist images when feature is represented by raw pixels and cnn learned feature☆64Updated 7 years ago
- Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling☆58Updated 3 years ago
- Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference, Gal et al. 2015☆36Updated 6 years ago
- Code and models for our paper "Risk-Aware Machine Learning Classifier for Skin Lesion Diagnosis"☆10Updated 8 months ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 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…☆78Updated 3 years ago
- Wasserstein Based Domain Adaptation Model☆46Updated 6 years ago
- ☆53Updated 6 years ago
- Learning Loss for Active Learning Pytorch Implementation,(reproduction)☆32Updated 5 years ago
- supervised and semi-supervised image classification with self-supervision (Keras)☆45Updated 4 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆60Updated 6 years ago
- Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).☆32Updated 4 years ago