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

Yuankai Teng, Xiaoping Zhang, Zhu Wang, Lili Ju; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:1-16

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

Didem Kochan, Zheng Zhang, Xiu Yang; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:17-32

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SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks

Ziyu Chen, Yingzhou Li, Xiuyuan Cheng; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:33-48

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Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits

Jiahao Yao, Haoya Li, Marin Bukov, Lin Lin, Lexing Ying; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:49-64

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

Kookjin Lee, Nathaniel Trask, Panos Stinis; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:65-80

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MURANA: A Generic Framework for Stochastic Variance-Reduced Optimization

Laurent Condat, Peter Richtarik; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:81-96

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Optimal denoising of rotationally invariant rectangular matrices

Emanuele Troiani, Vittorio Erba, FLORENT KRZAKALA, Antoine Maillard, Lenka Zdeborova; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:97-112

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

Sixin Zhang; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:113-128

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Natural Compression for Distributed Deep Learning

Samuel Horvóth, Chen-Yu Ho, Ludovit Horvath, Atal Narayan Sahu, Marco Canini, Peter Richtarik; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:129-141

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Error-in-variables modelling for operator learning

Ravi Patel, Indu Manickam, Myoungkyu Lee, Mamikon Gulian; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:142-157

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Data adaptive RKHS Tikhonov regularization for learning kernels in operators

Fei Lu, Quanjun Lang, Qingci An; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:158-172

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Stochastic and Private Nonconvex Outlier-Robust PCAs

Tyler Maunu, Chenyu Yu, Gilad Lerman; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:173-188

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

Tan Minh Nguyen, Richard Baraniuk, Robert Kirby, Stanley Osher, Bao Wang; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:189-204

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

Tao Luo, Zheng Ma, Zhiwei Wang, Zhiqin John Xu, Yaoyu Zhang; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:205-214

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Error Estimates for the Deep Ritz Method with Boundary Penalty

Johannes Müller, Marius Zeinhofer; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:215-230

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Notes on Exact Boundary Values in Residual Minimisation

Johannes Müller, Marius Zeinhofer; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:231-240

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Online Weak-form Sparse Identification of Partial Differential Equations

Daniel A.Messenger, Emiliano Dall’Anese, David Bortz; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:241-256

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

Arthur Jacot, Franck Gabriel, Francois Ged, Clement Hongler; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:257-270

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Hierarchical partition of unity networks: fast multilevel training

Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric Cyr; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:271-286

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Concentration of Random Feature Matrices in High-Dimensions

Zhijun Chen, Hayden Schaeffer, Rachel Ward; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:287-302

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SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning

Yuege Xie, Robert Shi, Hayden Schaeffer, Rachel Ward; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:303-318

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A Machine Learning Enhanced Algorithm for the Optimal Landing Problem

Yaohua Zang, Jihao Long, Xuanxi Zhang, Wei Hu, Weinan E, Jiequn Han; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:319-334

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Adaptive sampling methods for learning dynamical systems

Zichen Zhao, Qianxiao Li; Proceedings of Mathematical and Scientific Machine Learning, PMLR 190:335-350

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