Date: 11.01 ~ 11.04
Venue: A7-101
Zoom: 787 662 9899
Password: BIMSA
Organizer:
Zuoqiang Shi (史作强, YMSC & BIMSA)
会议日程
2024.11.01
09:00-09:30 陈景润
Machine learning-based methods for PDEs: The issue of condition number
09:30-10:00 王冀鲁
Convergence of renormalized finite element methods for heat flow of harmonic maps
10:00-10:30 杜洁
High order bound preserving discontinuous Galerkin methods for compressible multi-species flow with chemical reactions
11:00-11:30 李铁军
AI Assisted Computational Biology: Two Case Studies
11:30-12:00 周沛劼
Dissecting spatiotemporal single-cell transcriptomics data combining dynamical models and generative AI
14:00-14:30 申立勇
Real-time Tool Path Planning Using Deep Learning for Subtractive Manufacturing
14:30-15:00 苏春梅
Structure-preserving parametric finite element methods for geometric flows
15:00-15:30 李宏杰
The effective construction on elastic metamaterials
16:00-16:30 焦雨领
DRM Revisited: A Complete Error Analysis
16:30-17:00 魏珂
On the convergence of policy gradient methods
2024.11.02
09:00-09:30 沈捷
Navier-Stokes Equations: decoupled numerical schemes and beyond
09:30-10:00 段玉萍
Curvature Regularization Method for Non-Line-of-Sight Imaging
10:00-10:30 许现民
The Onsager principle and structure preserving numerical schemes
11:00-11:30 董国志
Learning-informed differential equation models and their applications
11:30-12:00 邱凌云
Sediment Measurement: an Inverse Problem Formulation
14:00-14:30 马征
深度学习方法求解 PDE 反问题
14:30-15:00 梁鑫
An RADI-type method for stochastic continuous-time algebraic Riccati equations
2024.11.03
09:00-09:30 金石
偏微分方程的量子计算
09:30-10:00 邓东灵
面向量子，面向 AI，面向量子 AI
10:00-10:30 蒋凯
Quasiperiodic Systems: Algorithms, Analysis and Applications
11:00-11:30 熊涛
基于神经网络的多尺度动理学方程动态区域分解方法
11:30-12:00 朱毅
A temporal difference learning method for solving high-dimensional PIDEs
14:00-14:30 王筱平
A fully-decoupled second-order-in-time and unconditionally energy stable scheme for a phase-field model of two phase flow with variable density
14:30-15:00 龚世华
Some convergence results for RAS-Imp and RAS-PML for the non-trapping Helmholtz problems
15:00-15:30 刘锦鹏
Provably Efficient Adiabatic Learning for Quantum-Classical Dynamics
16:00-16:30 孙赫
从受损观测中学习生成式图像先验
16:30-17:00 吴磊
Inductive Biases of Deep Convolutional Networks: A Theoretical Perspective
2024.11.04
09:00-09:30 杨武岳
基于多尺度建模的机器学习正反问题求解
09:30-10:00 熊繁升
求解一维双曲守恒律方程的机器学习方法研究
10:00-10:30 杨朔
Convergent finite element approximation of liquid crystals polymer networks
11:00-11:30 包承龙
Some recent progress in cryo-EM: towards establishing the data cycle
