justinuliu / WAAL

WAAL

Wasserstein Adversarial Active Learning A pytorch implementation of Deep Active Learning: Unified and Principled Method for Query and Training

Prerequisites

• Pytorch >=1.0, Torchvision >=0.2
• Scikit-learn >= 0.19.1

Models

• 'Test.py': Active Learning model
• 'query_startegies/wasserstien_adversarial.py': Model for WAAL

How to cite

@InProceedings{pmlr-v108-shui20a,
  title = 	 {Deep Active Learning: Unified and Principled Method for Query and Training},
  author = 	 {Shui, Changjian and Zhou, Fan and Gagn\'e, Christian and Wang, Boyu},
  booktitle = 	 {Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics},
  pages = 	 {1308--1318},
  year = 	 {2020},
  editor = 	 {Chiappa, Silvia and Calandra, Roberto},
  volume = 	 {108},
  series = 	 {Proceedings of Machine Learning Research},
  address = 	 {Online},
  month = 	 {26--28 Aug},
  publisher = 	 {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v108/shui20a/shui20a.pdf},
  url = 	 {http://proceedings.mlr.press/v108/shui20a.html},
}