22.08.06 Tutorial: Ying Nian Wu
Bio
Ying Nian Wu is currently a professor in Department of Statistics, UCLA. He received his A.M. degree and Ph.D. degree in statistics from Harvard University in 1994 and 1996 respectively. He was an assistant professor in the Department of Statistics, University of Michigan from 1997 to 1999. He joined UCLA in 1999. He has been a full professor since 2006. Wu’s research areas include generative modeling, representation learning, computer vision, computational neuroscience, and bioinformatics.
Title
A Tutorial on Generative Models
Abstract
In this tutorial, I will review recent generative models, including GAN, VAE, flow-based models, energy-based models, diffusion/score-based models. I will go over key equations and algorithms for learning these models, and I will also explain the connections between these models.
Replay (需要科学上网和观看密码)
Slides
小朱老师按
吴英年老师，江湖人称“老吴”，与朱松纯院长合作了将近 30 年，毕业于哈佛大学，师从大统计家Don Rubin（就是那个发明了 EM 算法和第一次在统计上讲清楚了什么是因果的大佬；你见过搞理论的人有 30w 的 citation 么）。吴老师从 90s 就开始研究生成式算法，和朱院长合著了多篇有影响力的 generative vision 的文章，包括朱院长的代表作之一 FRAME（第一篇把纹理讲清楚的文章）和获得 Marr 奖提名的 Active Basis（吸引我当年去朱院长实验室的文章）。实事求是的说，这年头火的 EBM 都是吴老师当年玩剩下的~老吴至今仍旧活跃在科研一线，一作发统计顶刊（感兴趣的童鞋可以去读读 A tale of three probabilistic families: discriminative, descriptive and generative models）。吴老师的机器学习课在 UCLA 是非常有名的，看老吴推公式是一种享受，而且老吴可以把各个模型之间的关系讲的非常清楚（在油管上绝对找不到！）。希望童鞋们能在这次 2 小时的 tutorial 中感受到数学的魅力。
Photos
Poster
