huyng / incertaeLinks
Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
☆70Updated 5 years ago
Alternatives and similar repositories for incertae
Users that are interested in incertae are comparing it to the libraries listed below
Sorting:
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- ☆239Updated 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
- Dropout as Regularization and Bayesian Approximation☆58Updated 6 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆116Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆273Updated 3 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.☆18Updated 2 years ago
- ☆109Updated 4 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆45Updated 5 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆206Updated 3 years ago
- Implementation of Deep evidential regression paper☆57Updated 4 years ago
- My implementation of https://arxiv.org/abs/1910.02600 in pytorch. Based on https://github.com/aamini/evidential-deep-learning☆10Updated 4 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆56Updated 2 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆105Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆114Updated 3 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 6 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆44Updated 11 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Reusable BatchBALD implementation☆79Updated last year
- ☆42Updated 2 years ago
- Awesome Domain Adaptation Python Toolbox☆356Updated last year
- " Weight Uncertainty in Neural Networks"☆49Updated 7 years ago
- Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods☆22Updated 4 years ago
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆24Updated 4 years ago
- A PyTorch implementation of BatchBALD on the MNIST dataset☆13Updated 5 years ago
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆30Updated 5 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆104Updated 4 years ago
- AM207 project: dissect aleatoric and epistemic uncertainty☆90Updated 5 years ago