BIMSA >
控制理论和非线性滤波讨论班
控制理论和非线性滤波讨论班
Fast, Multimodal, Derivative-Free Bayes Inference with Fisher-Rao Gradient Flows
Fast, Multimodal, Derivative-Free Bayes Inference with Fisher-Rao Gradient Flows
组织者
丘成栋
演讲者
康家熠
时间
2024年10月02日 20:00 至 21:00
地点
Online
摘要
In this group meeting I will report two papers, 1 Sampling via gradient flows in the space of probability measures. https://arxiv.org/abs/2310.03597 2 Efficient, multimodal, and derivative-free Bayesian inference with Fisher-Rao gradient flows. https://arxiv.org/abs/2406.17263
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.