Note: The links are for the slides.
Regularization for learning/inverse problems with nonlocal dependence
Nonparametric inference and statistical learning
- 2023/6, HUST Statistical learning and inverse problems from interacting particle systems
- 2022/11, AMS JHU Statistical learning and inverse problems from interacting particle systems
- 2022/9, Fields Institute, Toronto Nonparametric learning of interaction kernels in interacting particle systems
- 2022/8, BIMCR mini-course: Mathematical foundations of learning kernels in Operators
- 2022/3, UMass Amherst Learning interacting kernels in mean-field equations and DARTR
- 2021/8, Europe Dynamics Day Learning interacting kernels in mean-field equations
- 2021/7, SIAM AN21 Clustering prediction of opinion dynamics
- 2021/5, SIAM DS21 Learning interacting kernels of mean-field equations of 1st-order particle systems
- 2019/11, UPenn Nonparametric inference of interaction laws in particles/agent systems
- 2019/2, UMD Nonparametric inference of interaction laws in particles/agent systems
Stochastic model reduction and data assimilation
- 2022/7, SIAM AN22, Pittsburg Shock trace prediction by reduced models for stochastic Burgers equation
- 2022/7, Virginia Tech Stochastic ROM closure Accurate ROMs for Industrial Applications at Virginia Tech
- 2022/6, CAS-AMSS A statistical learning perspective of data-driven model reduction
- 2021/3, Virginia Tech and Univ. of Kansas Stochastic model reduction of nonlinear dynamics by inference
- 2020/9, 2nd Symposium on Machine Learning and Dynamical Systems Data-driven model reduction
for stochastic Burgers equations
- 2019/5, SIAM-DS, Snowbird,Utah SMR: from nonlinear Galerkin to parametric inference
- 2019/5, SIAM Snowbird, Utah Data assimilation with stochastic model reduction
- 2018/4, SIAM UQ, Grove Garden, CA Data assimilation with stochastic reduced models
- 2017/11, Banff, Canada Data assimilation with stochastic model reduction
SPDE in Climate modeling