BIMSA-Tsinghua Seminar on Machine Learning and Differential Equations

 

Differential equations can describe various natural and social phenomena. Machine learning is a powerful and effective way in solving and discovering differential equations. The aim of this seminar is to invite eminent scholars from home and abroad to deliver talks on machine learning and differential equations every week.

 

Time

08:50 - 12:15, every Thursday, from Sept. 1, 2022

 

Frequency

Weekly

 

Organizers

Fansheng Xiong, Wuyue Yang, Wen-An Yong, Yi Zhu

Our Publications Related to Machine Learning

 

Location

Room: BIMSA 1129B

ZOOM: 537 192 5549 (PW: BIMSA)

 

Schedule

Date Speaker Title Video
Jan 05, 2023 Gang Yan Inferring the Structure and Dynamics of Complex Networked Systems Video
Dec 22, 2022 Jiequn Han Learning Nonlocal Constitutive Models with Neural Operators Video
Dec 15, 2022 Zhi-Qin John Xu 探索神经网络解微分方程的理论与应用 Video
Dec 08, 2022 Qianxiao Li Approximation Theory of Deep Learning from the Dynamical Systems Viewpoint Video
Dec 01, 2022 Jianwei Ma 基于深度学习的地震勘探速度建模 Video
Nov 24, 2022 Tao Zhou Deep adaptive sampling for numerical PDEs Video
Nov 17, 2022 Wei Zhu Symmetry-preserving machine learning for computer vision, scientific computing, and distribution learning Video
Nov 10, 2022 Xiaoli Chen Data driven method to learn the stochastic dynamical systems and its application in polymer dynamics Video
Nov 03, 2022 Zhiqiang Cai Neural Nets and Numerical PDEs Video
Oct 27, 2022 Lu Lu Learning operators using deep neural networks for multiphysics, multiscale & multifidelity problems Video
Oct 20, 2022 David Bortz Data-Driven Modeling and Learning Using the Weak Form Video
Oct 13, 2022 Wei Cai Deep Neural Network Algorithms for Oscillatory Flows, Causality Operators, and High Dimensional Fokker-Planck Equations Video
Oct 13, 2022 Ameya D. Jagtap Physics-Informed Neural Networks for Scientific Computations: Algorithms and Applications Video
Sep 29, 2022 Han Wang Deep learning molecular dynamics simulation Video
Sep 22, 2022 Hao Sun Data-driven Discovery of Physics Video
Sep 15, 2022 Zuoqiang Shi Differential Equation Model for Semi-supervised Learning Video
Sep 08, 2022 George Em Karniadakis From Neural PDEs to Neural Operators: Blending data and physics for fast predictions Video