675587 event 1721859425 1721859556 <![CDATA[Ph.D. Dissertation Defense - Tianrong Chen]]> Title:  Bridging the Connection between Deep Learning and Stochastic Optimal Control

Committee:

Dr. Evangelos Theodorou, AE, Chair, Advisor

Dr. Matthieu Bloch, ECE, Chair, Co-Advisor

Dr. Justin Romberg, ECE

Dr. Molei Tao, Math

Dr. Shuangfei Zhai, Apple

Dr. Yao Xie, ISyE

]]> Generative models have gained significant popularity in recent years, and Stochastic Optimal Control soc has also advanced rapidly in parallel. This thesis addresses the prob- lem of understanding dynamical generative models from the perspective of Stochastic Opti- mal Control, thereby providing insights from the well-established Stochastic Optimal Con- trol theory. Additionally, it explores the challenges of high-dimensional Stochastic Optimal Control by leveraging deep learning techniques. Through this dual approach, the research aims to enhance the theoretical understanding and practical application of generative mod- els and Stochastic Optimal Control in complex, high-dimensional environments.

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