clabrugere / evidential-deeplearningLinks
Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neural network.
☆28Updated 2 years ago
Alternatives and similar repositories for evidential-deeplearning
Users that are interested in evidential-deeplearning are comparing it to the libraries listed below
Sorting:
- An implementation of the state-of-the-art Deep Active Learning algorithms☆104Updated 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
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆144Updated 2 years ago
- Evidential Deep Learning in PyTorch☆63Updated 2 years ago
- ☆108Updated 2 years ago
- Reusable BatchBALD implementation☆79Updated last year
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- ☆16Updated 3 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- ☆38Updated 4 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆113Updated 3 years ago
- C-Mixup for NeurIPS 2022☆73Updated last year
- Pseudo-labeling for tabular data☆23Updated last year
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- ☆110Updated 4 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 years ago
- Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets☆97Updated 11 months ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- An easy-to-use interface for measuring uncertainty and robustness.☆14Updated 4 years ago
- This repository contains an official implementation of LPBNN.☆38Updated 2 years ago
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆29Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Implementation of Deep evidential regression paper☆58Updated 4 years ago
- Large-scale uncertainty benchmark in deep learning.☆63Updated 4 months ago
- A PyTorch toolkit with 8 popular deep active learning query methods implemented.☆90Updated 4 years ago
- The official codebase for Predictive Inference with Feature Conformal Prediction☆37Updated 2 years ago
- Deep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)☆44Updated 3 years ago