This repo contains our code for paper:
Lingkai Kong, Jimeng Sun and Chao Zhang, SDE-Net: Equipping Deep Neural Network with Uncertainty Estimates, ICML2020.
cd MNIST
Training vanilla ResNet:
python resnet_mnist.py
Evaluation:
python test_detection.py --pre_trained_net save_resnet_mnist/final_model --network resnet --dataset mnist --out_dataset svhn
Training MC-dropout:
python resnet_droput_mnist.py
Evaluation:
python test_detection.py --pre_trained_net save_resnet_dropout_mnist/final_model --network mc_dropout --dataset mnist --out_dataset svhn
Training SDE-Net:
python sdenet_mnist.py
Evaluation:
python test_detection.py --pre_trained_net save_sdenet_mnist/final_model --network sdenet --dataset mnist --out_dataset svhn
cd SVHN
Training vanilla ResNet:
python resnet_svhn.py
Evaluation:
python test_detection.py --pre_trained_net save_resnet_svhn/final_model --network resnet --dataset svhn --out_dataset cifar10
Training MC-dropout:
python resnet_droput_svhn.py
Evaluation:
python test_detection.py --pre_trained_net save_resnet_dropout_svhn/final_model --network mc_dropout --dataset svhn --out_dataset cifar10
Training SDE-Net:
python sdenet_mnist.py
Evaluation:
python test_detection.py --pre_trained_net save_sdenet_svhn/final_model --network sdenet --dataset svhn --out_dataset cifar10
cd YearMSD
Download and unzip the dataset from https://archive.ics.uci.edu/ml/machine-learning-databases/00203/
Training MC-dropout:
python DNN_mc.py
Evaluation:
python test_detection_mc.py --pre_trained_net save_mc_msd/final_model
Training SDE-Net:
python SDE_regression.py
Evaluation:
python test_detection_sde.py --pre_trained_net save_sdenet_msd/final_model
Please cite the following paper if you find this repo helpful. Thanks!
@inproceedings{kong2020sde,
title={SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates},
author={Kong, Lingkai and Sun, Jimeng and Zhang, Chao},
booktitle={International Conference on Machine Learning},
year={2020}
}