A Mathematical Introduction to Generative Adversarial Nets (GAN)
Generative Adversarial Nets (GAN) have received considerable attention since the 2014 groundbreaking work by Goodfellow et al. Such attention has led to an explosion in new ideas, techniques and applications of GANs. To better understand GANs we need to understand the mathematical foundation behind them. This paper attempts to provide an overview of GANs from a mathematical point of view. Many students in mathematics may find the papers on GANs more difficulty to fully understand because most of them are written from computer science and engineer point of view. The aim of this paper is to give more mathematically oriented students an introduction to GANs in a language that is more familiar to them.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
An Introduction to Image Synthesis with Generative Adversarial Nets
There has been a drastic growth of research in Generative Adversarial Nets (GANs) in the past few years. Proposed in 2014, GAN has been applied to various applications such as computer vision and natural language process…
Image GenerationImage-to-Image TranslationTranslationActivation Maximization Generative Adversarial Nets
Class labels have been empirically shown useful in improving the sample quality of generative adversarial nets (GANs). In this paper, we mathematically study the properties of the current variants of GANs that make use o…
DiversityAn Introduction to Person Re-identification with Generative Adversarial Networks
Person re-identification is a basic subject in the field of computer vision. The traditional methods have several limitations in solving the problems of person illumination like occlusion, pose variation and feature vari…
Person Re-IdentificationGenerative Adversarial Network: Some Analytical Perspectives
Ever since its debut, generative adversarial networks (GANs) have attracted tremendous amount of attention. Over the past years, different variations of GANs models have been developed and tailored to different applicati…
Generative Adversarial NetworkInception Score, Label Smoothing, Gradient Vanishing and -log(D(x)) Alternative
In this article, we mathematically study several GAN related topics, including Inception score, label smoothing, gradient vanishing and the -log(D(x)) alternative. --- An advanced version is included in arXiv:1703.02…