Reduced order model for kinetic and transport problems
Speaker: Zhichao Peng (MSU) Dates: 2023/02/24 Zoom link: click this link Abstract: Numerical simulation plays an important role in various engineering and scientific problems. Reduced order model (ROM), a technique to reduce degrees of freedom needed in numerical simulations, is…
Dynamical System Learning via Neural Networks
Speaker: Zhongshu Xu (OSU) Dates: 2023/02/09 Abstract: This talk will briefly review Prof Dongbin Xiu’s work on dynamical system learning and Neural Networks. First, I will discuss the connection between Euler forward scheme and ResNet, and why multi-step ResNet can…
Introduction to Bayesian Neural Networks.
Speaker: Tatsuoka Caroline (OSU) Dates: 2023/02/02 Abstract: I will be reviewing the Bayesian Neural Network framework. With sufficient data, current deep learning technologies offer a tool to better understand and predict dynamical systems behavior. However, uncertainty in predictions can arise…
Sketch-and-solve approaches to k-means clustering by semidefinite programming
Speaker: Kaiying Xie (OSU) Dates: 2023/01/27 Abstract: We introduce a sketch-and-solve approach to speed up the Peng-Wei semidefinite relaxation of k-means clustering. When the data is appropriately separated we identify the k-means optimal clustering. Otherwise, our approach provides a high-confidence…
Monotone meshfree methods for linear elliptic equations in non-divergence form via nonlocal relaxation
Speaker: Qihao Ye (UCSD) Dates: 2023/01/20 Zoom link: click this link Abstract: We design a monotone meshfree finite difference method for linear elliptic equations in the non-divergence form on point clouds via a nonlocal relaxation method. The key idea is…