Abstract: Generative Adversarial Networks (Gans) have attracted intense interest lately in computer vision, image generation, and simulation of financial time series data. In this talk, I will first provide a gentle review of the mathematics framework behind GANs. I will then proceed to discuss a few challenges in GANs training from an analytical perspective. I will finally report some recent progress for GANs training using a controlled SDE approach.
Bio：Dr. Xin Guo is the Coleman Fung Chair Professor in Financial Modeling at the University of California, Berkeley and the Director of the Risk Analytics & Data Analysis Research Lab.
Dr. Xin Guo's research lies broadly in the span of stochastic controls and games, mean-field games, machine learning, mathematical finance, and FinTech. She has co-authored more than 70 research publications and a book in Quantitative Trading which has been translated into Chinese and Japanese.
Dr. Xin Guo is co-editor-in-chief of Frontier in Mathematical Finance, and the associate editor of many leading journals including Mathematical Finance, Operations Research, Mathematics, and Financial Economics. She is also the co-founder and co-chair of Women in Financial Engineering.
Zoom：
https://us05web.zoom.us/j/4481524376?pwd=eVpyVjBTQ1FQMWM5Y3JzU3VZQ2oxZz09
Meeting ID：448 152 4376
Password：230302
