#### Note:

1) Author(s) might revise the paper based on comments they receive during the conference.

2) Authors with ‘*’ will present on the conference.

3) Plenary lecture will be specially marked.

4) Schedule can be downloaded here.

### Aug 15th, 2022, Monday (GMT+8)

8:20am- 8:35am#### Opening Address

8:35am- 9:35am#### Plenary Lecture

**Learning operators using deep neural networks for multiphysics, multiscale, & multifidelity problems**

Lu Lu (University of Pennsylvania)

**Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver**

Yuankai Teng (University of South Carolina)*; Xiaoping Zhang (Wuhan University); Zhu Wang (University of South Carolina); Lili Ju (University of South Carolina)

**A Quantum-Inspired Hamiltonian Monte Carlo Method for Missing Data Imputation**

Didem Kochan (Lehigh University)*; Zheng Zhang (UC Santa Barbara); Xiu Yang (Lehigh University)

**SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks**

Ziyu Chen (Duke University)*; Yingzhou Li (Fudan University); Xiuyuan Cheng (Duke University)

**Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits**

Jiahao Yao (University of California, Berkeley)*; Haoya Li (Stanford University); Marin Bukov (University of California, Berkeley); Lin Lin (University of California, Berkeley); Lexing Ying (Stanford University)

**Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling**

Kookjin Lee (Arizona State University)*; Nathaniel A Trask (Sandia National Laboratories)*; Nathaniel A Trask (Sandia National Laboratories)*; Panos Stinis (Pacific Northwest National Laboratory)

**MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization**

Laurent CONDAT (KAUST)*; Peter Richtarik (KAUST)

**Optimal denoising of rotationally invariant rectangular matrices**

Emanuele Troiani (EPFL); Vittorio Erba (EPFL)*; FLORENT KRZAKALA (EPFL); Antoine Maillard (ETH Zurich); Lenka Zdeborova (EPFL)

**On the Nash equilibrium of moment-matching GANs for stationary Gaussian processes**

Sixin Zhang (IRIT)*

### Aug 16th, 2022, Tuesday (GMT+8)

8:30am- 9:10am**Natural Compression for Distributed Deep Learning**

Samuel Horváth (MBZUAI)*; Chen-Yu Ho (KAUST); Ludovit Horvath (Comenius University); Atal N Sahu (KAUST); Marco Canini (KAUST); Peter Richtarik (KAUST)

**Error-in-variables modelling for operator learning**

Ravi Patel (Sandia National Laboratories)*; Indu Manickam (Sandia National Laboratories); Myoungkyu Lee (University of Alabama); Mamikon Gulian (Sandia National Laboratories)

**Data adaptive RKHS Tikhonov regularization for learning kernels in operators**

Fei Lu (Johns Hopkins University)*; Quanjun Lang (Johns Hopkins University); Qingci An (Johns Hopkins University)

**Stochastic and Private Nonconvex Outlier-Robust PCA**

Tyler Maunu (Brandeis University)*; Chenyu Yu (Princeton University); Gilad Lerman (University of Minnesota)

**Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization**

Tan Minh Nguyen (University of California, Los Angeles); Richard Baraniuk (Rice University); Robert Kirby (University of Utah); Stanley Osher (UCLA); Bao Wang (University of Utah)*

#### Plenary Lecture

**Deep Approximation via Deep Learning**

Zuowei Shen (National University of Singapore)

**An Upper Limit of Decaying Rate with Respect to Frequency in Linear Frequency Principle Model**

Tao Luo (Shanghai Jiaotong University); Zheng Ma (Shanghai Jiao Tong University); Zhiwei Wang (Shanghai Jiaotong University)*; Zhiqin John Xu (Shanghai Jiao Tong University); Yaoyu Zhang (Shanghai Jiao Tong University)

**Error Estimates for the Deep Ritz Method with Boundary Penalty**

Marius Zeinhofer (Simula Research Laboratory)*; Johannes Müller (Max Planck Institute for Mathematics in the Sciences)

**Notes on Exact Boundary Values in Residual Minimisation**

Marius Zeinhofer (Simula Research Laboratory); Johannes Müller (Max Planck Institute for Mathematics in the Sciences)*

### Aug 17th, 2022, Wednesday (GMT+8)

8:30am- 9:10am**Online Weak-form Sparse Identification of Partial Differential Equations**

Daniel A Messenger (University of Colorado Boulder)*; Emiliano Dall'Anese (Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder); David Bortz (University of Colorado Boulder)

**Freeze and Chaos: NTK views on DNN Normalization, Checkerboard and Boundary Artifacts**

Arthur Jacot (EPFL)*; Franck Gabriel (EPFL); François Ged (EPFL); Clement Hongler (EPFL)

**Hierarchical partition of unity networks: fast multilevel training**

Nathaniel A Trask (Sandia National Laboratories)*; Amelia Henriksen (Sandia National Laboratories); Carianne Martinez (Sandia National Laboratories); Eric Cyr (Sandia National Laboratories)

**Concentration of Random Feature Matrices in High-Dimensions**

Zhijun Chen (Carnegie Mellon University); Hayden Schaeffer (Carnegie Mellon University )*; Rachel Ward (University of Texas)

**SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning**

Yuege Xie (University of Texas at Austin)*; Robert Shi (University of Texas at Austin); Hayden Schaeffer (Carnegie Mellon University); Rachel Ward (University of Texas)

#### Plenary Lecture

**Rational Materials Design**

Konstantin Novoselov (National University of Singapore)

**A Machine Learning Enhanced Algorithm for the Optimal Landing Problem**

Yaohua Zang (Zhejiang Uinversity)*; Jihao Long (Princeton University); Xuanxi Zhang (Peking University); Wei Hu (Princeton University); Weinan E (Princeton University); Jiequn Han (Flatiron Institute)

**Adaptive sampling methods for learning dynamical systems**

Zichen Zhao (National University of Singapore)*; Qianxiao Li (National University of Singapore)