SEMINARS
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"Kernel Mode Decomposition and Programmable/Interpretable Regression Networks" by Owhadi Et. Al.
- Lei Zhang, Institute of Natural Sciences, Shanghai Jiao Tong University
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2019.12.04, 12:20-13:50
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Research Progress on High Gain Laser Fusion
- Jie Zhang, Chinese Academy of Sciences & Shanghai Jiao Tong University
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2019.11.27, 15:30-16:30
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Physics-Informed Neural Networks for Solving Forward and Inverse Stochastic Problems
- Ling Guo, Shanghai Normal University
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2019.11.27, 12:20-13:50
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P53 Dynamics and Cell Fate Decision
- Feng Liu, Nanjing University
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2019.11.26, 14:00-15:00
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Shape and Topology Optimization Based on Shape Gradients
- Shengfeng Zhu, East China Normal University
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2019.11.26, 10:00-11:00
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Reducing Blood Viscosity, Suppressing Turbulence with Magnetic Field to Prevent Heart Attack and Stroke
- Rongjia Tao, Temple University
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2019.11.22, 10:00-11:00
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Int Deep: A Deep Learning Initialized Iterative Method for Nonlinear Problems
- Jianguo Huang, School of Mathematical Sciences, and LSC-MOE, Shanghai Jiao Tong University
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2019.11.20, 12:20-13:50
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Mathematical Modeling of Circadian Rhythms
- Ling Yang,Soochow University
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2019.11.19, 14:00-15:00
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The Dilemma and Breakthrough of Artificial Intelligence
- Zhiming Zheng, Beihang University
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2019.11.16, 16:00-17:30
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New Universe and New World: Interpretation of the 2019 Nobel Prize in Physics
- Pengjie Zhang, School of Physics and Astronomy, Shanghai Jiao Tong University
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2019.11.13, 16:00-17:30
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Theoretical Understanding of Stochastic Gradient Descent in Deep Learning
- Zhanxing Zhu, Peking University
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2019.11.13, 12:20-13:50
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The General Principle for Constructing Split Contraction Algorithm for Convex Optimization
- Bingsheng He,Southern University of Science and Technology
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2019.11.12, 14:00-15:00
