The goal of this project is to implement an outlier detection method. The method implemented here is BiGAN/EGBAD anomaly detection. Codes and Models are available for PyTorch
The implemented model is BIGAN/EGBAD. It has been tested on two different dataset: CIFAR10 and MNIST. The model was trained using OneVsAll protocol