Haizhao Yang

Xiangxiong Zhang

J. Comput. Appl. Math., 2024

Towards Better Generalization: Weight Decay Induces Low-rank Bias for Neural Networks.

[BibT_eX]

[DOI]

Ke Chen

Chugang Yi

CoRR, 2024

Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method.

[BibT_eX]

[DOI]

Gareth Hardwick

Senwei Liang

CoRR, 2024

Accelerating Multi-Block Constrained Optimization Through Learning to Optimize.

[BibT_eX]

[DOI]

Ling Liang

Cameron Austin

CoRR, 2024

Optimal Neural Network Approximation for High-Dimensional Continuous Functions.

[BibT_eX]

[DOI]

Ayan Maiti

Michelle Michelle

CoRR, 2024

Vertex Exchange Method for a Class of Quadratic Programming Problems.

[BibT_eX]

[DOI]

Ling Liang

Kim-Chuan Toh

CoRR, 2024

Nesterov's Accelerated Jacobi-Type Methods for Large-scale Symmetric Positive Semidefinite Linear Systems.

[BibT_eX]

[DOI]

CoRR, 2024

FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model.

[BibT_eX]

[DOI]

Zezheng Song

Jiaxin Yuan

CoRR, 2024

On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization.

[BibT_eX]

[DOI]

Ling Liang

CoRR, 2024

Finite Expression Method for Learning Dynamics on Complex Networks.

[BibT_eX]

[DOI]

Zezheng Song

CoRR, 2024

Lottery Ticket Hypothesis for Attention Mechanism in Residual Convolutional Neural Network<sup>*</sup>.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Neural Network Approximation for Pessimistic Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., June, 2023

Stationary Density Estimation of Itô Diffusions Using Deep Learning.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., February, 2023

Deep Operator Learning Lessens the Curse of Dimensionality for PDEs.

[BibT_eX]

[DOI]

Ke Chen

Trans. Mach. Learn. Res., 2023

Nearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces.

[BibT_eX]

[DOI]

CoRR, 2023

let data talk: data-regularized operator learning theory for inverse problems.

[BibT_eX]

[DOI]

Ke Chen

CoRR, 2023

A Finite Expression Method for Solving High-Dimensional Committor Problems.

[BibT_eX]

[DOI]

Zezheng Song

Maria K. Cameron

CoRR, 2023

Spectral Clustering via Orthogonalization-Free Methods.

[BibT_eX]

[DOI]

Qiyuan Pang

CoRR, 2023

Finite Expression Methods for Discovering Physical Laws from Data.

[BibT_eX]

[DOI]

Zhongyi Jiang

CoRR, 2023

Deep Learning via Neural Energy Descent.

[BibT_eX]

[DOI]

CoRR, 2023

Convergence Analysis of the Deep Galerkin Method for Weak Solutions.

[BibT_eX]

[DOI]

CoRR, 2023

Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives.

[BibT_eX]

[DOI]

Yahong Yang

Yang Xiang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation.

[BibT_eX]

[DOI]

SIAM J. Numer. Anal., August, 2022

From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

A Fast Petrov-Galerkin Spectral Method for the Multidimensional Boltzmann Equation Using Mapped Chebyshev Functions.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2022

Simultaneous neural network approximation for smooth functions.

[BibT_eX]

[DOI]

Sean Hon

Neural Networks, 2022

Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Integral Autoencoder Network for Discretization-Invariant Learning.

[BibT_eX]

[DOI]

Yong Zheng Ong

J. Mach. Learn. Res., 2022

Linear-scaling selected inversion based on hierarchical interpolative factorization for self Green's function for modified Poisson-Boltzmann equation in two dimensions.

[BibT_eX]

[DOI]

J. Comput. Phys., 2022

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?

[BibT_eX]

[DOI]

CoRR, 2022

Accelerating Numerical Solvers for Large-Scale Simulation of Dynamical System via NeurVec.

[BibT_eX]

[DOI]

CoRR, 2022

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network.

[BibT_eX]

[DOI]

CoRR, 2022

Finite Expression Method for Solving High-Dimensional Partial Differential Equations.

[BibT_eX]

[DOI]

Senwei Liang

CoRR, 2022

IAE-Net: Integral Autoencoders for Discretization-Invariant Learning.

[BibT_eX]

[DOI]

Yong Zheng Ong

CoRR, 2022

Connecting Optimization and Generalization via Gradient Flow Path Length.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Network Architecture Beyond Width and Depth.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Network Approximation in Terms of Intrinsic Parameters.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

2021

Rapid Application of the Spherical Harmonic Transform via Interpolative Decomposition Butterfly Factorization.

[BibT_eX]

[DOI]

James Bremer

Ze Chen

SIAM J. Sci. Comput., 2021

Deep Network Approximation for Smooth Functions.

[BibT_eX]

[DOI]

SIAM J. Math. Anal., 2021

Neural network approximation: Three hidden layers are enough.

[BibT_eX]

[DOI]

Neural Networks, 2021

Deep Network With Approximation Error Being Reciprocal of Width to Power of Square Root of Depth.

[BibT_eX]

[DOI]

Neural Comput., 2021

Machine learning for prediction with missing dynamics.

[BibT_eX]

[DOI]

J. Comput. Phys., 2021

SelectNet: Self-paced learning for high-dimensional partial differential equations.

[BibT_eX]

[DOI]

Yiqi Gu

Chao Zhou

J. Comput. Phys., 2021

Structure probing neural network deflation.

[BibT_eX]

[DOI]

Yiqi Gu

J. Comput. Phys., 2021

ReLU Network Approximation in Terms of Intrinsic Parameters.

[BibT_eX]

[DOI]

CoRR, 2021

Multiscale and Nonlocal Learning for PDEs using Densely Connected RNNs.

[BibT_eX]

[DOI]

Ricardo A. Delgadillo

Jingwei Hu

CoRR, 2021

Simultaneous Neural Network Approximations in Sobolev Spaces.

[BibT_eX]

[DOI]

Sean Y. Hon

CoRR, 2021

Solving PDEs on Unknown Manifolds with Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2021

A fast Petrov-Galerkin spectral method for the multi-dimensional Boltzmann equation using mapped Chebyshev functions.

[BibT_eX]

[DOI]

CoRR, 2021

Optimal Approximation Rate of ReLU Networks in terms of Width and Depth.

[BibT_eX]

[DOI]

CoRR, 2021

Reproducing Activation Function for Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Blending Pruning Criteria for Convolutional Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

2020

Interpolative Decomposition Butterfly Factorization.

[BibT_eX]

[DOI]

Qiyuan Pang

Kenneth L. Ho

SIAM J. Sci. Comput., 2020

Error bounds for deep ReLU networks using the Kolmogorov-Arnold superposition theorem.

[BibT_eX]

[DOI]

Hadrien Montanelli

Neural Networks, 2020

A Fast Algorithm for Multiresolution Mode Decomposition.

[BibT_eX]

[DOI]

Gao Tang

Multiscale Model. Simul., 2020

A hierarchical butterfly LU preconditioner for two-dimensional electromagnetic scattering problems involving open surfaces.

[BibT_eX]

[DOI]

Yang Liu

J. Comput. Phys., 2020

Int-Deep: A deep learning initialized iterative method for nonlinear problems.

[BibT_eX]

[DOI]

Jianguo Huang

Haoqin Wang

J. Comput. Phys., 2020

Multidimensional phase recovery and interpolative decomposition butterfly factorization.

[BibT_eX]

[DOI]

J. Comput. Phys., 2020

Frequency-chirprate reassignment.

[BibT_eX]

[DOI]

Digit. Signal Process., 2020

Efficient Attention Network: Accelerate Attention by Searching Where to Plug.

[BibT_eX]

[DOI]

CoRR, 2020

Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory.

[BibT_eX]

[DOI]

Tao Luo

CoRR, 2020

Deep Network Approximation with Discrepancy Being Reciprocal of Width to Power of Depth.

[BibT_eX]

[DOI]

CoRR, 2020

SelectNet: Learning to Sample from the Wild for Imbalanced Data Training.

[BibT_eX]

[DOI]

Yunru Liu

Tingran Gao

Proceedings of Mathematical and Scientific Machine Learning, 2020

Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

DIANet: Dense-and-Implicit Attention Network.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Nonlinear approximation via compositions.

[BibT_eX]

[DOI]

Neural Networks, 2019

A unified framework for oscillatory integral transforms: When to use NUFFT or butterfly factorization?

[BibT_eX]

[DOI]

J. Comput. Phys., 2019

Deep Network Approximation Characterized by Number of Neurons.

[BibT_eX]

[DOI]

CoRR, 2019

Generative Imaging and Image Processing via Generative Encoder.

[BibT_eX]

[DOI]

Lin Chen

CoRR, 2019

CASS: Cross Adversarial Source Separation via Autoencoder.

[BibT_eX]

[DOI]

Yong Zheng Ong

Charles K. Chui

CoRR, 2019

2018

Recursive Diffeomorphism-Based Regression for Shape Functions.

[BibT_eX]

[DOI]

Jieren Xu

Ingrid Daubechies

SIAM J. Math. Anal., 2018

Phase-Space Sketching for Crystal Image Analysis Based on Synchrosqueezed Transforms.

[BibT_eX]

[DOI]

SIAM J. Imaging Sci., 2018

Diffusion Forecasting Model with Basis Functions from QR-Decomposition.

[BibT_eX]

[DOI]

John Harlim

Álvaro Vázquez-Mayagoitia

J. Nonlinear Sci., 2018

ELSI: A unified software interface for Kohn-Sham electronic structure solvers.

[BibT_eX]

[DOI]

Chao Yang

Volker Blum

Comput. Phys. Commun., 2018

Drop-Activation: Implicit Parameter Reduction and Harmonic Regularization.

[BibT_eX]

[DOI]

Senwei Liang

Yuehaw Khoo

CoRR, 2018

Non-Oscillatory Pattern Learning for Non-Stationary Signals.

[BibT_eX]

[DOI]

CoRR, 2018

2017

Removal of Canvas Patterns in Digital Acquisitions of Paintings.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2017

Interpolative Butterfly Factorization.

[BibT_eX]

[DOI]

Yingzhou Li

SIAM J. Sci. Comput., 2017

Preconditioning Orbital Minimization Method for Planewave Discretization.

[BibT_eX]

[DOI]

Multiscale Model. Simul., 2017

A cubic scaling algorithm for excited states calculations in particle-particle random phase approximation.

[BibT_eX]

[DOI]

J. Comput. Phys., 2017

Spectrum Slicing for Sparse Hermitian Definite Matrices Based on Zolotarev's Functions.

[BibT_eX]

[DOI]

Yingzhou Li

CoRR, 2017

2015

Quantitative Canvas Weave Analysis Using 2-D Synchrosqueezed Transforms: Application of time-frequency analysis to art investigation.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2015

Crystal Image Analysis Using 2D Synchrosqueezed Transforms.

[BibT_eX]

[DOI]

Multiscale Model. Simul., 2015

A Multiscale Butterfly Algorithm for Multidimensional Fourier Integral Operators.

[BibT_eX]

[DOI]

Yingzhou Li

Multiscale Model. Simul., 2015

Butterfly Factorization.

[BibT_eX]

[DOI]

Multiscale Model. Simul., 2015

2014

Synchrosqueezed Curvelet Transform for Two-Dimensional Mode Decomposition.

[BibT_eX]

[DOI]

SIAM J. Math. Anal., 2014

2013

Synchrosqueezed Wave Packet Transform for 2D Mode Decomposition.

[BibT_eX]

[DOI]