Mathematical analysis of loss function of GAN and its loss function variants
International Journal of Advanced Technology and Engineering Exploration · 2022
The generative model is a strong unsupervised learning method for learning any distribution of data and has experienced considerable success in a short amount of time.The idea behind such models is to generate new data instances or configurations.They can generate new photos of different types of objects that look like real ones.They enable users to provide information about the problem to the learning algorithm using prior distributions, structured models, independence graphs, probabilistic reasoning, Markov assumptions, and latent variables.It includes the data's distribution and indicates the likelihood of a certain example.For instance, the models used to determine the subsequent word in a series belong to the category of generative models because each word in the sequence is assigned a probability.These generative models include mixtures of multinomial, mixtures of experts, naïve Research