huyng / incertaeLinks
Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
☆69Updated 5 years ago
Alternatives and similar repositories for incertae
Users that are interested in incertae are comparing it to the libraries listed below
Sorting:
- 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
- This repository reimplemented "MC Dropout" by tensorflow 2.0 Eager Extension.☆18Updated 2 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆156Updated 2 years ago
- ☆108Updated 3 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Learning error bars for neural network predictions☆70Updated 5 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆115Updated 4 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆51Updated 5 years ago
- " Weight Uncertainty in Neural Networks"☆49Updated 7 years ago
- ☆238Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆43Updated 7 months ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Implementation of Deep evidential regression paper☆57Updated 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☆30Updated 5 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆43Updated 4 years ago
- ☆38Updated 6 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Updated 5 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…☆23Updated 4 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 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
- This repo contains a PyTorch implementation of the paper: "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles"☆13Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- ☆42Updated 6 years ago
- Reusable BatchBALD implementation☆79Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆77Updated 3 years ago
- My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"☆138Updated 7 years ago