Direct Method Based on Gaussian Approximation
组织者
丘成栋
演讲者
康家熠
时间
2024年04月23日 15:00 至 15:30
地点
Online
摘要
In this talk, for nonlinear filtering problems, we proposed a direct method based on fixed-Gaussian distributions. In this algorithm, all time-consuming computations can be removed by leveraging deep learning.
演讲者介绍
Jiayi Kang received his Ph.D. in Mathematics from Tsinghua University in 2024. He joined the Beijing Institute of Mathematical Sciences and Applications (BIMSA) as an Assistant Researcher in July 2024, and became an Assistant Professor at the Hetao Institute for Mathematical and Interdisciplinary Sciences (HIMIS) in November 2025.
His research focuses on the intersection of deep learning, nonlinear filtering, and computational biology. His main research interests include: neural network-based filtering algorithms and their mathematical foundations, sampling methods in Wasserstein geometry, nonlinear filtering theory (including the Yau-Yau method) and its applications in climate science and other fields, as well as computational genomics and evolutionary system modeling. He is committed to solving complex problems in science and engineering using mathematical and machine learning methods.