中国科学院数学与系统科学研究院
数学研究所
学术报告
动力系统讨论班
Speaker: 祝爱卿（新加坡国立大学）
Title: Learning dynamical models from data
Time&Venue: 2024.1.2（周四）9:00-10:00 & 南楼N702
Abstract: With the rapid expansion of observational data, deep learning are increasingly utilized to discover unknown dynamics from data. In this presentation, we will first discuss fidelity in learning dynamics. Specifically, we will highlight how structure-preserving methods enhance fidelity, and provide rigorous quantification of the fidelity of learning models. Furthermore, we will explore the challenges and solutions involved in learning dynamics from data across various modalities.
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