美国纽约州立大学石溪分校计算机系顾险峰教授来校做学术
The fundamental principle behind generative adversarial networks (GANs) is to manipulate probability measures, such as to transform distributions, measure the Wasserstein distance between distributions and so on. Optimal mass transportation theory offers a geometric framework to handle probability measures, which gives a unique point of view of interpreting GAN models. In this talk, the connect...
活动时间：
2017-06-08 13:30
主讲人：雷娜
