This seminar aims to introduce cutting-edge research of Data Science, especially, the application of Data Science in scientific problems and the "science" part of Data Science, such as understanding deep learning. Welcome to contact Zhiqin Xu (xuzhiqin@sjtu.edu.cn).
Stochastic Gradient Descent for Inverse Problems
Bangti Jin, University College London, UK
2020.12.02, 09:00-10:00

A Dynamical Central Limit Theorem for Shallow Neural Networks
Zhengdao Chen, New York University, USA
2020.11.20, 10:00-11:00

Fourier Neural Operator for Parametric Partial Differential Equations
Zongyi Li, The California Institute of Technology, USA
2020.11.09, 10:00-11:00

Inferring Principles of Cell Cycle Regulation from Lineage Correlations in Cancer Cells
Shaon Chakrabarti, National Centre for Biological Research at the Tata Institute of Fundamental Research, India
2020.10.29, 15:00-16:00

Integrating Molecular Modeling with Machine Learning and High-Performance Computing
Linfeng Zhang, Beijing Institute of Big Data Research
2020.10.27, 10:45-11:45

Learning & Exploiting Low-Dimensional Structure in High-Dimensional Data
Didong Li, Princeton University
2020.10.22, 10:00-11:00

Solving Group Synchronization via Optimization and Spectral Methods
Shuyang Ling, New York University
2020.10.15, 10:00-11:00

Dynamic Incorporation of Multiple in Silico Functional Annotations Empowers Rare Variant Association Analysis of Large Whole-Genome Sequencing Studies at Scale
Zilin Li and Xihao Li, Harvard T. H. Chan School of Public Health
2020.10.13, 09:00-10:00

Community Detection in Sparse Latent Space Models
Fengnan Gao, Fudan University, China
2020.09.24, 09:00-10:00

Learning Over Parameterized Neural Networks: from Neural Tangent Kernel to Mean-Field Analysis
Yuan Cao, University of California, Los Angeles, USA
2020.09.17, 10:00-11:00

Exploring Energy Landscapes by Normalizing Flows
Hao Wu, Tongji University, China
2020.09.11, 14:00-15:00

A Statistical Mechanics Theory of Generalization in Kernel Regression and Wide Neural Networks
Cengiz Pehlevan, Harvard University
2020.06.26, 10:00-11:00