Uncertainty_Mnist

Uncertainty estimation on Mnist dataset

This is a PyTorch implementation of Dropout Uncertainty on Mnist. The experiment setting is based on Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning at 5.2 Model Uncertainty in Classification Tasks.

Installation

1. Install Pytorch Pytorch

conda install pytorch torchvision -c pytorch

2. Clone this repository

git clone https://github.com/andyhahaha/Uncertainty_Mnist

Usage

1. Train Lenet standard and Lenet dropout

python main.py --mode 0

2. Test Lenet standard and Lenet dropout

python main.py --mode 1

3. Test the Lenet dropout on rotated Mnist image

python main.py --mode 2

Result

These results show the uncertainty of different rotated digits.

0	1
2	3
4	5
6	7
8	9