# UQ

**Repository Path**: swing148/UQ

## Basic Information

- **Project Name**: UQ
- **Description**: No description available
- **Primary Language**: Python
- **License**: CC0-1.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-11-23
- **Last Updated**: 2024-05-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Uncertainty-Aware Neural Network Training Scripts

#### This repository contains several scripts of Uncertainty-Aware Neural Network Trainining. We apply codes to several datasets and upload codes in Jupyter Notebooks with execution details.

### Folder 'CAM' conains scripts of the following paper: 
Kabir, H.M., 2023. Reduction of Class Activation Uncertainty with Background Information. arXiv preprint arXiv:2305.03238.

### Folder 'Direct Intervals' conains scripts of the following paper: 
Kabir, H.D., Khosravi, A., Kavousi-Fard, A., Nahavandi, S. and Srinivasan, D., 2021. Optimal uncertainty-guided neural network training. Applied Soft Computing, 99, p.106878.

### Folder 'UQ Considering Similarity, Sensitivity and Error Sensitivity' conains scripts of the following paper: 
Kabir, H.M., Mondal, S.K., Khanam, S., Khosravi, A., Rahman, S., Qazani, M.R.C., Alizadehsani, R., Asadi, H., Mohamed, S., Nahavandi, S. and Acharya, U.R., 2023. Uncertainty Aware Neural Network from Similarity and Sensitivity. arXiv preprint arXiv:2304.14925.

### Folder 'UQ Considering Similarity and Sensitivity' conains scripts of the following paper: 
Kabir, H.D., Khosravi, A., Nahavandi, D. and Nahavandi, S., 2020, July. Uncertainty quantification neural network from similarity and sensitivity. In 2020 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.

### Folder 'UQ using KNN for classification' conains scripts of the following paper: 
Kabir, H.D., Khanam, S., Khozeimeh, F., Khosravi, A., Mondal, S.K., Nahavandi, S. and Acharya, U.R., 2022. Aleatory-aware deep uncertainty quantification for transfer learning. Computers in Biology and Medicine, 143, p.105246.