LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning (NeurIPS 2021)

Requirements

To install requirements:

pip install -r requirements.txt

Training

To train the model(s) in the paper, run this command:

python main.py --data Cifar10 --method LADA

Evaluation

• Data will be downloaded to folder 'data'.
• Result will be recorded to folder 'Results'.

Results

Our model achieves the following performance on active learning settings:

Model name	FashionMNIST	SVHN	CIFAR-10	CIFAR-100
LADA	83.68%	75.72%	53.45%	46.92%