Schedule of Workshop on Mathematical Machine Learning and Application If you can not open the video link next to the title, try this one.
Dec. 14, Monday (EST)
Session 1 (Chair: Jinchao Xu, Co-chair: John Harlim)
Time (EST)	Invited Speaker	Title
9:50-10:00	Opening Remarks(Slides, Video)
10:00-11:00	Ingrid Daubechies	Low-dimensional Manifolds in High-dimensional Data Sets (Video)
11:00-12:00	Andrew Stuart	Learning Operators (Video)
12:00-13:00	John Urschel	Stress Minimization for Low Diameter Graphs (Video)
Session 2 (Chair: Pierre-Emmanual Jabin, Co-chair: Lu Lu)
14:00-15:00	George Em Karniadakis	DeepOnet - Theory-based Learning of General Nonlinear Multiscale Operators (Video)
15:00-16:00	Eric Darve	Reinforcement Learning for Combinatorial Control of Partial Differential Equations (Video)
16:00-17:00	Juncai He	Hierarchical and Multigrid Structures in Deep and Convolutional Neural Networks (Video)
Session 3 (Chair: Alberto Bressan, Co-chair: Haizhao Yang)
19:00-20:00	Weinan E	Machine Learning and PDEs (Video)
20:00-21:00	Zuowei Shen	Deep Approximation via Deep Learning (Video)
21:00-22:00	Bin Dong	Learning to Solve PDEs with Hypernetworks (Video)
Dec. 15, Tuesday (EST)
Session 4 (Chair: Ludmil Zikatanov, Co-chair: Jonathan Siegel)
10:00-11:00	Ronald DeVore	Neural Network Approximation: What we know and what you may not want to know (Video)
11:00-12:00	Gregery T. Buzzard	Computational Imaging without Cost: Plug and Play and Equilibrium Methods (Video)
12:00-13:00	Rachel Ward	Concentration for Matrix Products, and Convergence of Oja's Algorithm for Streaming PCA
Session 5 (Chair: Alexei Novikov, Co-Chair: John Harlim)
14:00-15:00	Thomas Y. Hou	High-Dimensional Bayesian Inference with Multiscale Invertible Generative Networks (MsIGN) (Video)
15:00-16:00	Lin Xiao	Statistical Preconditioning for Distributed Empirical Risk Minimization (Video)
16:00-17:00	Tyrus Berry	Optimal Bases for Data-Driven Forecasting (Video)
Session 6 (Chair: Leonid Berlyand, Co-chair: Tyrus Berry)
19:00-20:00	Jonathan Siegel	Optimal Approximation Rates for Neural Networks with Cosine and ReLU^k Activation Functions (Video)
20:00-21:00	Dimitris Giannakis	Quantum compiler for Classical Dynamical Systems (Video)
21:00-22:00	Zuoqiang Shi	PDE-based Models in Machine Learning (Video)
Dec. 16, Wednesday
Session 7 (Chair: Wenrui Hao, Co-chair: Tyrus Berry)
10:00-11:00	Peter Markowich	Selection Dynamics for Deep Neural Networks (Video)
11:00-12:00	Ji Hui	Self-supervised Deep Learning for Image Recovery (Video)
12:00-13:00	Mireille Boutin	Highly Likely Clusterable Data with No Cluster (Video)
Session 8 (Chair: Xiantao Li, Co-chair: Jonathan Siegel)
14:00-15:00	Andrea Bertozzi	Total Variation Minimization on Graphs for Semisupervised and Unsupervised Machine Learning
15:00-16:00	Christoph Schwab	Exponential Deep Neural Network Expression for Solution Sets of PDEs (Slides)
16:00-17:00	John Harlim	Machine Learning of Missing Dynamical Systems (Video)
Session 9 (Chair: John Harlim, Co-chair: Juncai He)
19:00-19:30	Poster	Brief introduction by each poster presenter
19:30-22:00		Presentation and discussion in individual zoom room