Computer Vision, Gans, Generative Adversarial, Generative Mo, Deep Learning.
variations that can describe the input data, the shape of z is usually smaller than x. Now, the question is how do we learn this feature representation (z)? How do we train this model? For that, we can add a decoder network on top of the extracted features and use L2 loss to train the model: This