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Colloquia & Seminars
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Home - ActivitiesSeminars of 2019
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*Friday 26 July, 10:00-11:00 am, Z301
Prof. Long Chen,(Univ of California at Irvine)
From differential equation solvers to first order convex optimization methods -
Friday 26 July, 10:00-11:00 am, N602
Associate Prof. Xiaosheng Zhuang,(City University of Hong Kong)
Directional Tensor Product Complex Tight Framelets: Construction and Application -
Thursday 25 July, 11:00-12:00 am, Z311
Prof. Zhening Li,(University of Portsmouth)
Orthogonal tensors and best rank one app roximation ratio -
Thursday 25 July, 10:00-11:00 am, Z311
Chao Ma,(Princeton University)
A-priori estimates of population risks for neural networks models -
Thursday 25 July, 9:00-10:00 am, Z311
Prof. Ran He,(Institute of Automation, Chinese Academy of Sciences)
Variational image analysis under limited computational resource -
Wednesday 24 July, 16:30-17:30 pm, Z311
朱升峰 副教授,(数学科学学院，华东师范大学)
Convergence analysis of mixed finite element approximations to shape gradients in shape optimization of flows -
Wednesday 24 July, 15:30-16:30 pm, Z311
Assistant Prof. Weiwei Hu,(Department of Mathematics, Oklahoma State University, USA)
An Approximating Control Design for Optimal Mixing via Fluid Flows -
Tuesday 2 July - Thursday 4 July, 14:00-17:00 pm, Z311
Celso Ribeiro,(Universidade Federal Fluminense)
Optimization with Metaheuristics -
Friday 19 July, 16:00-17:00 pm, N702
Prof. Tong Kang,(School of Data Science and Medium Intelligence, Communication University of China)
Fully Discrete T-ψ Finite Element Method to Solve a Nonlinear Induction Hardening Problem -
Friday 19 July, 15:00-16:00 pm, N702
Prof. Guizhen Lu,(School of Information and Communication Engineering, Communication University of China)
Surface Plasmon Polarization and Scattering Optical Near Field Microscopy -
Monday 15 July, 16:00-17:00 pm, N702
Prof. Ruchi Guo,(Department of Mathematics, Ohio S tate University, USA)
Immersed Finite Element Methods and the Applications in Interface Inverse Problems -
Monday 15 July, 15:10-16:10 pm, N602
Jiequn Han,(Princeton University, Department of Mathematics and PACM)
Uniformly Accurate Machine Learning Based Hydrodynamic Models for Kinetic Equations
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