Overview of Polya-Gamma Augmentation
If you've ever studied Bayesian inference, then you know that it can be quite complex. One of the most difficult tasks in Bayesian inference is finding the full-conditional distributions of posterior distributions in sampling algorithms like Markov chain Monte Carlo (MCMC). Luckily, there is a method called Polya-Gamma augmentation that can help simplify this task. In this article, we will discuss the basics of Polya-Gamma augmentation, how it is applied in
Latent optimisation is a technique used to improve the quality of samples produced by generative adversarial networks (GANs). GANs consist of a generator and a discriminator, and the goal is to train the generator to produce samples that are indistinguishable from real data. One way to improve the quality of these samples is to use latent optimisation to refine the latent source used by the generator.
What is Latent Optimisation?
Latent optimisation is a technique used in machine learning to
The Truncation Trick is a technique used in generative adversarial networks (GANs) to sample from a truncated normal distribution. This procedure was first introduced in a paper called Megapixel Size Image Creation with GAN and has since been used in other GAN models such as BigGAN.
What is a Generative Adversarial Network?
Before discussing the Truncation Trick, it is helpful to know what a GAN is. A GAN is a type of artificial intelligence that learns to generate new data after being traine