Computer Vision, Gans, Generative Adversarial, Generative Mo, Deep Learning.
a product of 1-d distributions using the chain rule: p(x) here represents the likelihood of image x and the right side represents the probability of the ith pixel value given all previous pixels. After defining this function, we maximize the likelihood of training data. This is how tractable