An easy-to-run implementation using PyTorch for the paper " Evidential Deep Learning to Quantify Classification Uncertainty ".
Requirements
- python 3.8.8
- numpy 1.19.2
- pytorch 1.7.1
- torchvision 0.8.2
- scikit-learn 0.24.1
- scikit-image 0.18.2
- scipy 1.6.2
Running
python main.py
Acc on valid dataset.
Model | MNIST |
---|---|
softmax | 0.9909 |
EDL using log | 0.9714 |
EDL using digamma | 0.9766 |
EDL using mse | 0.9745 |