lunayht / DBALwithImgDataLinks
Deep Bayesian Active Learning with Image Data by Gal et al. (ICML 2017)
☆44Updated 3 years ago
Alternatives and similar repositories for DBALwithImgData
Users that are interested in DBALwithImgData are comparing it to the libraries listed below
Sorting:
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆103Updated last year
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆141Updated 2 years ago
- A PyTorch toolkit with 8 popular deep active learning query methods implemented.☆87Updated 3 years ago
- This repository contains an official implementation of LPBNN.☆38Updated last year
- Wasserstein Adversarial Active Learning☆29Updated 4 years ago
- ☆40Updated 5 years ago
- ☆15Updated 4 years ago
- Code for "Deal: Deep Evidential Active Learning for Image Classification" (ICMLA 2020)☆21Updated 4 years ago
- Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets☆93Updated 7 months ago
- Pytorch implementation of Cost-Effective Active Learning for Deep Image Classification paper☆17Updated 5 years ago
- Generalizing to unseen domains via distribution matching☆72Updated 4 years ago
- An implementation of the BADGE batch active learning algorithm.☆205Updated last year
- ☆108Updated 3 years ago
- Official implementation of our paper: Towards Robust and Reproducible Active Learning using Neural Networks, accepted at CVPR 2022.☆67Updated last year
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 years ago
- Last-layer Laplace approximation code examples☆82Updated 3 years ago
- [CVPR2021] Task-Aware Variational Adversarial Active Learning☆41Updated last year
- My implementation of https://arxiv.org/abs/1910.02600 in pytorch. Based on https://github.com/aamini/evidential-deep-learning☆9Updated 4 years ago
- Reusable BatchBALD implementation☆78Updated last year
- Survey for Distribution Shift☆19Updated 4 years ago
- Reliability diagrams visualize whether a classifier model needs calibration☆150Updated 3 years ago
- using monte carlo dropout to have uncertainty estimation of predictions☆14Updated 5 years ago
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆31Updated 3 years ago
- ☆66Updated 5 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆68Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- ☆22Updated 3 years ago