报告题目：EPR-Net for Constructiong the Landscape of Biological Systems
报 告 人：李铁军 教授 (北京大学)
报告时间：2023年11月1日上午10：30-11：30
报告地点：数学科学学院A413 （腾讯会议 768-203-461）
内容简介：
We present the EPR-Net, a novel and effective deep learning approach that addresses a crucial challenge in biophysics: constructing potential landscapes for high-dimensional non-equilibrium steady-state (NESS) systems. The key idea of our approach is to utilize the fact that the negative potential gradient is the orthogonal projection of the driving force with respect to an inner product weighted by the steady-state distribution. Remarkably, the minimum of our proposed loss function coincides with the steady entropy production rate (EPR) formula in NESS theory. We also introduce an enhanced learning strategy for systems with small noise, and extend our unified framework to dimensionality reduction and state-dependent diffusion coefficients. The proposed approach is successfully applied to different biophysical examples.
报告人简介：李铁军，北京大学数学学院教授，国家级称号人才。研究领域为随机模型及算法，在复杂网络、生物体系随机动力学、单细胞转录组数据分析领域做出了重要贡献。
（撰稿：梁西银 审核：张国）
数学科学学院
2023年10月23日
