Data Science Plus Dynamical Systems: What Can We Learn?
报告人:段金桥教授,Illinois Institute of Technology 时间:2020年6月27日上午9:30
摘要:Observational datasets are abundant. Dynamical systems are mathematical models in engineering, medicine and science. Data are noisy and dynamical systems are often under random fluctuations (either
Gaussian or non-Gaussian noise). The interactions between data science and dynamical systems are becoming exciting. On the one hand, dynamical systems tools are valuable to extract information from datasets. On the other hand, data science techniques are indispensable for understanding dynamical behaviors with
observational data. I will present recent progress on extracting stochastic governing laws
and their stochastic dynamical information.