This repository implements the Adversarial Latent Autoencoder (ALAE) architecture from the CVPR 2020 paper. It combines autoencoder and GAN approaches to achieve both generative and representational capabilities. The method learns disentangled representations while maintaining the generative power of GANs. The implementation includes style mixing and reconstruction capabilities demonstrated on face datasets like FFHQ and CelebA-HQ.