Synchrosqueezed Wave Packet Transform for 2D Mode Decomposition. - Haizhao Yang; Lexing Ying (SIAM J. Imaging Sci., 2013)

Synchrosqueezed Curvelet Transform for Two-Dimensional Mode Decomposition. - Haizhao Yang; Lexing Ying (SIAM J. Math. Anal., 2014)

Butterfly Factorization. - Yingzhou Li; Haizhao Yang; Eileen R. Martin; Kenneth L. Ho; Lexing Ying (Multiscale Model. Simul., 2015)

A Multiscale Butterfly Algorithm for Multidimensional Fourier Integral Operators. - Yingzhou Li; Haizhao Yang; Lexing Ying (Multiscale Model. Simul., 2015)

Crystal Image Analysis Using 2D Synchrosqueezed Transforms. - Haizhao Yang; Jianfeng Lu 001; Lexing Ying (Multiscale Model. Simul., 2015)

Quantitative Canvas Weave Analysis Using 2-D Synchrosqueezed Transforms: Application of time-frequency analysis to art investigation. - Haizhao Yang; Jianfeng Lu 001; William P. Brown; Ingrid Daubechies; Lexing Ying (IEEE Signal Process. Mag., 2015)

Spectrum Slicing for Sparse Hermitian Definite Matrices Based on Zolotarev's Functions. - Yingzhou Li; Haizhao Yang (CoRR, 2017)

A cubic scaling algorithm for excited states calculations in particle-particle random phase approximation. - Jianfeng Lu 001; Haizhao Yang (J. Comput. Phys., 2017)

Preconditioning Orbital Minimization Method for Planewave Discretization. - Jianfeng Lu 001; Haizhao Yang (Multiscale Model. Simul., 2017)

Interpolative Butterfly Factorization. - Yingzhou Li; Haizhao Yang (SIAM J. Sci. Comput., 2017)

Removal of Canvas Patterns in Digital Acquisitions of Paintings. - Bruno Cornelis; Haizhao Yang; Alex Goodfriend; Noelle Ocon; Jianfeng Lu 001; Ingrid Daubechies (IEEE Trans. Image Process., 2017)

Non-Oscillatory Pattern Learning for Non-Stationary Signals. - Jieren Xu; Yitong Li; David B. Dunson; Ingrid Daubechies; Haizhao Yang (CoRR, 2018)

Drop-Activation: Implicit Parameter Reduction and Harmonic Regularization. - Senwei Liang; Yuehaw Khoo; Haizhao Yang (CoRR, 2018)

ELSI: A unified software interface for Kohn-Sham electronic structure solvers. - Victor Wen-zhe Yu; Fabiano Corsetti; Alberto García; William P. Huhn; Mathias Jacquelin; Weile Jia; Björn Lange; Lin Lin 001; Jianfeng Lu 001; Wenhui Mi; Ali Seifitokaldani; Álvaro Vázquez-Mayagoitia; et al. (Comput. Phys. Commun., 2018)

Diffusion Forecasting Model with Basis Functions from QR-Decomposition. - John Harlim; Haizhao Yang (J. Nonlinear Sci., 2018)

Phase-Space Sketching for Crystal Image Analysis Based on Synchrosqueezed Transforms. - Jianfeng Lu 001; Haizhao Yang (SIAM J. Imaging Sci., 2018)

Recursive Diffeomorphism-Based Regression for Shape Functions. - Jieren Xu; Haizhao Yang; Ingrid Daubechies (SIAM J. Math. Anal., 2018)

CASS: Cross Adversarial Source Separation via Autoencoder. - Yong Zheng Ong; Charles K. Chui; Haizhao Yang (CoRR, 2019)

Generative Imaging and Image Processing via Generative Encoder. - Lin Chen; Haizhao Yang (CoRR, 2019)

Deep Network Approximation Characterized by Number of Neurons. - Zuowei Shen; Haizhao Yang; Shijun Zhang (CoRR, 2019)

A unified framework for oscillatory integral transforms: When to use NUFFT or butterfly factorization? - Haizhao Yang (J. Comput. Phys., 2019)

Nonlinear approximation via compositions. - Zuowei Shen; Haizhao Yang; Shijun Zhang (Neural Networks, 2019)

DIANet: Dense-and-Implicit Attention Network. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Haizhao Yang (AAAI, 2020)

Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise. - Senwei Liang; Zhongzhan Huang; Mingfu Liang; Haizhao Yang (AAAI, 2020)

SelectNet: Learning to Sample from the Wild for Imbalanced Data Training. - Yunru Liu; Tingran Gao; Haizhao Yang (MSML, 2020)

Deep Network Approximation with Discrepancy Being Reciprocal of Width to Power of Depth. - Zuowei Shen; Haizhao Yang; Shijun Zhang (CoRR, 2020)

Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory. - Tao Luo; Haizhao Yang (CoRR, 2020)

Efficient Attention Network: Accelerate Attention by Searching Where to Plug. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang (CoRR, 2020)

Frequency-chirprate reassignment. - Xiangxiang Zhu; Haizhao Yang; Zhuosheng Zhang 002; Jinghuai Gao; Naihao Liu (Digit. Signal Process., 2020)

Multidimensional phase recovery and interpolative decomposition butterfly factorization. - Ze Chen; Juan Zhang; Kenneth L. Ho; Haizhao Yang (J. Comput. Phys., 2020)

Int-Deep: A deep learning initialized iterative method for nonlinear problems. - Jianguo Huang; Haoqin Wang; Haizhao Yang (J. Comput. Phys., 2020)

A hierarchical butterfly LU preconditioner for two-dimensional electromagnetic scattering problems involving open surfaces. - Yang Liu 179; Haizhao Yang (J. Comput. Phys., 2020)

A Fast Algorithm for Multiresolution Mode Decomposition. - Gao Tang; Haizhao Yang (Multiscale Model. Simul., 2020)

Error bounds for deep ReLU networks using the Kolmogorov-Arnold superposition theorem. - Hadrien Montanelli; Haizhao Yang (Neural Networks, 2020)

Interpolative Decomposition Butterfly Factorization. - Qiyuan Pang; Kenneth L. Ho; Haizhao Yang (SIAM J. Sci. Comput., 2020)

Blending Pruning Criteria for Convolutional Neural Networks. - Wei He 025; Zhongzhan Huang; Mingfu Liang; Senwei Liang; Haizhao Yang (ICANN (4), 2021)

Reproducing Activation Function for Deep Learning. - Senwei Liang; Liyao Lyu; Chunmei Wang; Haizhao Yang (CoRR, 2021)

Optimal Approximation Rate of ReLU Networks in terms of Width and Depth. - Zuowei Shen; Haizhao Yang; Shijun Zhang (CoRR, 2021)

A fast Petrov-Galerkin spectral method for the multi-dimensional Boltzmann equation using mapped Chebyshev functions. - Jingwei Hu; Xiaodong Huang; Jie Shen 001; Haizhao Yang (CoRR, 2021)

Solving PDEs on Unknown Manifolds with Machine Learning. - Senwei Liang; Shixiao W. Jiang; John Harlim; Haizhao Yang (CoRR, 2021)

Simultaneous Neural Network Approximations in Sobolev Spaces. - Sean Y. Hon; Haizhao Yang (CoRR, 2021)

Multiscale and Nonlocal Learning for PDEs using Densely Connected RNNs. - Ricardo A. Delgadillo; Jingwei Hu; Haizhao Yang (CoRR, 2021)

ReLU Network Approximation in Terms of Intrinsic Parameters. - Zuowei Shen; Haizhao Yang; Shijun Zhang (CoRR, 2021)

Structure probing neural network deflation. - Yiqi Gu; Chunmei Wang; Haizhao Yang (J. Comput. Phys., 2021)

SelectNet: Self-paced learning for high-dimensional partial differential equations. - Yiqi Gu; Haizhao Yang; Chao Zhou 010 (J. Comput. Phys., 2021)

Machine learning for prediction with missing dynamics. - John Harlim; Shixiao W. Jiang; Senwei Liang; Haizhao Yang (J. Comput. Phys., 2021)

Deep Network With Approximation Error Being Reciprocal of Width to Power of Square Root of Depth. - Zuowei Shen; Haizhao Yang; Shijun Zhang (Neural Comput., 2021)

Neural network approximation: Three hidden layers are enough. - Zuowei Shen; Haizhao Yang; Shijun Zhang (Neural Networks, 2021)

Deep Network Approximation for Smooth Functions. - Jianfeng Lu 001; Zuowei Shen; Haizhao Yang; Shijun Zhang (SIAM J. Math. Anal., 2021)

Rapid Application of the Spherical Harmonic Transform via Interpolative Decomposition Butterfly Factorization. - James Bremer; Ze Chen; Haizhao Yang (SIAM J. Sci. Comput., 2021)

Deep Network Approximation in Terms of Intrinsic Parameters. - Zuowei Shen; Haizhao Yang; Shijun Zhang (ICML, 2022)

Neural Network Architecture Beyond Width and Depth. - Shijun Zhang; Zuowei Shen; Haizhao Yang (NeurIPS, 2022)

Connecting Optimization and Generalization via Gradient Flow Path Length. - Fusheng Liu; Haizhao Yang; Soufiane Hayou; Qianxiao Li (CoRR, 2022)

IAE-Net: Integral Autoencoders for Discretization-Invariant Learning. - Yong Zheng Ong; Zuowei Shen; Haizhao Yang (CoRR, 2022)

Finite Expression Method for Solving High-Dimensional Partial Differential Equations. - Senwei Liang; Haizhao Yang (CoRR, 2022)

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang; Liang Lin (CoRR, 2022)

Accelerating Numerical Solvers for Large-Scale Simulation of Dynamical System via NeurVec. - Zhongzhan Huang; Senwei Liang; Hong Zhang; Haizhao Yang; Liang Lin (CoRR, 2022)

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning? - Songyang Han; Sanbao Su; Sihong He; Shuo Han 002; Haizhao Yang; Fei Miao (CoRR, 2022)

Linear-scaling selected inversion based on hierarchical interpolative factorization for self Green's function for modified Poisson-Boltzmann equation in two dimensions. - Yihui Tu; Qiyuan Pang; Haizhao Yang; Zhenli Xu (J. Comput. Phys., 2022)

Integral Autoencoder Network for Discretization-Invariant Learning. - Yong Zheng Ong; Zuowei Shen; Haizhao Yang (J. Mach. Learn. Res., 2022)

Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons. - Shijun Zhang; Zuowei Shen; Haizhao Yang (J. Mach. Learn. Res., 2022)

Simultaneous neural network approximation for smooth functions. - Sean Y. Hon; Haizhao Yang (Neural Networks, 2022)

A Fast Petrov-Galerkin Spectral Method for the Multidimensional Boltzmann Equation Using Mapped Chebyshev Functions. - Jingwei Hu; Xiaodong Huang; Jie Shen 001; Haizhao Yang (SIAM J. Sci. Comput., 2022)

From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality. - Fusheng Liu; Haizhao Yang; Soufiane Hayou; Qianxiao Li (Trans. Mach. Learn. Res., 2022)

The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation. - Qiang Du 001; Yiqi Gu; Haizhao Yang; Chao Zhou 010 (SIAM J. Numer. Anal., 2022)

Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives. - Yahong Yang; Haizhao Yang; Yang Xiang (NeurIPS, 2023)

Convergence Analysis of the Deep Galerkin Method for Weak Solutions. - Yuling Jiao; Yanming Lai; Yang Wang 020; Haizhao Yang; Yunfei Yang 002 (CoRR, 2023)

Deep Learning via Neural Energy Descent. - Wenrui Hao; Chunmei Wang; Xingjian Xu; Haizhao Yang (CoRR, 2023)

Finite Expression Methods for Discovering Physical Laws from Data. - Zhongyi Jiang; Chunmei Wang; Haizhao Yang (CoRR, 2023)

Spectral Clustering via Orthogonalization-Free Methods. - Qiyuan Pang; Haizhao Yang (CoRR, 2023)

let data talk: data-regularized operator learning theory for inverse problems. - Ke Chen; Chunmei Wang; Haizhao Yang (CoRR, 2023)

Nearly Optimal Approximation Rates for Deep Super ReLU Networks on Sobolev Spaces. - Yahong Yang; Yue Wu; Haizhao Yang; Yang Xiang (CoRR, 2023)

Deep Operator Learning Lessens the Curse of Dimensionality for PDEs. - Ke Chen; Chunmei Wang; Haizhao Yang (Trans. Mach. Learn. Res., 2023)

Stationary Density Estimation of Itô Diffusions Using Deep Learning. - Yiqi Gu; John Harlim; Senwei Liang; Haizhao Yang (SIAM J. Numer. Anal., 2023)

Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning. - Fan Chen; Jianguo Huang; Chunmei Wang; Haizhao Yang (SIAM J. Sci. Comput., 2023)

Neural Network Approximation for Pessimistic Offline Reinforcement Learning. - Di Wu; Yuling Jiao; Li Shen 008; Haizhao Yang; Xiliang Lu (AAAI, 2024)

Lottery Ticket Hypothesis for Attention Mechanism in Residual Convolutional Neural Network*. - Zhongzhan Huang; Senwei Liang; Mingfu Liang; Wei He 025; Haizhao Yang; Liang Lin (ICME, 2024)

Finite Expression Method for Learning Dynamics on Complex Networks. - Zezheng Song; Chunmei Wang; Haizhao Yang (CoRR, 2024)

FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model. - Zezheng Song; Jiaxin Yuan; Haizhao Yang (CoRR, 2024)

Nesterov's Accelerated Jacobi-Type Methods for Large-scale Symmetric Positive Semidefinite Linear Systems. - Ling Liang; Qiyuan Pang; Kim-Chuan Toh; Haizhao Yang (CoRR, 2024)

Vertex Exchange Method for a Class of Quadratic Programming Problems. - Ling Liang; Kim-Chuan Toh; Haizhao Yang (CoRR, 2024)

Optimal Neural Network Approximation for High-Dimensional Continuous Functions. - Ayan Maiti; Michelle Michelle; Haizhao Yang (CoRR, 2024)

Accelerating Multi-Block Constrained Optimization Through Learning to Optimize. - Ling Liang; Cameron Austin; Haizhao Yang (CoRR, 2024)

Towards Better Generalization: Weight Decay Induces Low-rank Bias for Neural Networks. - Ke Chen; Chugang Yi; Haizhao Yang (CoRR, 2024)

On the convergence of orthogonalization-free conjugate gradient method for extreme eigenvalues of Hermitian matrices: A Riemannian optimization interpretation. - Shixin Zheng; Haizhao Yang; Xiangxiong Zhang (J. Comput. Appl. Math., 2024)

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. - Hao Liu 028; Haizhao Yang; Minshuo Chen; Tuo Zhao; Wenjing Liao (J. Mach. Learn. Res., 2024)

Reinforced Inverse Scattering. - Hanyang Jiang; Yuehaw Khoo; Haizhao Yang (SIAM J. Sci. Comput., 2024)

What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning? - Songyang Han; Sanbao Su; Sihong He; Shuo Han 002; Haizhao Yang; Shaofeng Zou; Fei Miao (Trans. Mach. Learn. Res., 2024)

On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization. - Ling Liang; Haizhao Yang (Trans. Mach. Learn. Res., 2024)

A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering. - Qiyuan Pang; Haizhao Yang (J. Sci. Comput., 2024)

LLMs Meet Finance: Fine-Tuning Foundation Models for the Open FinLLM Leaderboard. - Varun Rao; Youran Sun; Mahendra Kumar; Tejas Mutneja; Agastya Mukherjee; Haizhao Yang (IDS, 2025)

Solving high-dimensional partial integral differential equations: The finite expression method. - Gareth Hardwick; Senwei Liang; Haizhao Yang (J. Comput. Phys., 2025)

A Finite Expression Method for Solving High-Dimensional Committor Problems. - Zezheng Song; Maria K. Cameron; Haizhao Yang (SIAM J. Sci. Comput., 2025)

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport. - Di Wu; Ling Liang; Haizhao Yang (CoRR, 2025)

Curse of Dimensionality in Neural Network Optimization. - Sanghoon Na; Haizhao Yang (CoRR, 2025)

Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors. - Sikai Huang; Yixin Berry Wen; Tara Adusumilli; Kusum Choudhary; Haizhao Yang (CoRR, 2025)

From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs. - Rohan Bhatnagar; Ling Liang; Krish Patel; Haizhao Yang (CoRR, 2025)

OptimAI: Optimization from Natural Language Using LLM-Powered AI Agents. - Raghav Thind; Youran Sun; Ling Liang; Haizhao Yang (CoRR, 2025)

Quantum Circuit Encodings of Polynomial Chaos Expansions. - Junaid Aftab; Christoph Schwab; Haizhao Yang; Jakob Zech (CoRR, 2025)

Efficient Kilometer-Scale Precipitation Downscaling with Conditional Wavelet Diffusion. - Chugang Yi; Minghan Yu; Weikang Qian; Yixin Wen; Haizhao Yang (CoRR, 2025)