/SEC-CGAN

Primary LanguageJupyter NotebookMIT LicenseMIT

SEC-CGAN

Tested on PyTorch 1.13.1.

conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
pip install -r requirements.txt

Example: training the model for 20 epochs

python train.py --n_epochs 20

Citation: Hao Zhen, Yucheng Shi, Jidong J. Yang, Javad Mohammadpour Vehni. Co-supervised learning paradigm with conditional generative adversarial networks for sample-efficient classification[J]. Applied Computing and Intelligence, 2023, 3(1): 13-26. doi: 10.3934/aci.2023002

Co-supervised learning paradigm with conditional generative adversarial networks for sample-efficient classification