Feature Preserving Lossy Image Compression Using Nonlinear PDE's. - Tony F. Chan; Haomin Zhou 001 (Data Compression Conference, 1998)

Total Variation Improved Wavelet Thresholding in Image Compression. - Tony F. Chan; Haomin Zhou 001 (ICIP, 2000)

ENO-Wavelet Transforms for Piecewise Smooth Functions. - Tony F. Chan; Haomin Zhou 001 (SIAM J. Numer. Anal., 2002)

Total Variation Wavelet-Based Medical Image Denoising. - Yang Wang 020; Haomin Zhou 001 (Int. J. Biomed. Imaging, 2006)

Wiener Chaos expansions and numerical solutions of randomly forced equations of fluid mechanics. - Thomas Y. Hou 001; Wuan Luo; Boris Rozovskii; Haomin Zhou 001 (J. Comput. Phys., 2006)

Total Variation Wavelet Inpainting. - Tony F. Chan; Jianhong Shen; Haomin Zhou 001 (J. Math. Imaging Vis., 2006)

Adaptive multiresolution mesh refinement for the solution of evolution PDEs. - Sachin Jain; Panagiotis Tsiotras; Haomin Zhou 001 (CDC, 2007)

Total Variation Wavelet Thresholding. - Tony F. Chan; Haomin Zhou 001 (J. Sci. Comput., 2007)

A Hierarchical Multiresolution Adaptive Mesh Refinement for the Solution of Evolution PDEs. - Sachin Jain; Panagiotis Tsiotras; Haomin Zhou 001 (SIAM J. Sci. Comput., 2008)

Iterative Filtering as an Alternative Algorithm for Empirical Mode Decomposition. - Luan Lin; Yang Wang 020; Haomin Zhou 001 (Adv. Data Sci. Adapt. Anal., 2009)

Wiener Chaos Expansion and Simulation of Electromagnetic Wave Propagation Excited by a Spatially Incoherent Source. - Majid Badieirostami; Ali Adibi; Haomin Zhou 001; Shui-Nee Chow (Multiscale Model. Simul., 2009)

Wavelets and PDE Techniques in Image Processing, A Quick Tour of. - Haomin Zhou 001; Tony F. Chan; Jianhong Shen (Encyclopedia of Complexity and Systems Science, 2009)

Randomization of Forcing in Large Systems of PDEs for Improvement of Energy Estimates. - Chia Ying Lee; Boris L. Rozovskii; Haomin Zhou 001 (Multiscale Model. Simul., 2010)

Shortest paths through 3-dimensional cluttered environments. - Jun Lu; Yancy Diaz-Mercado; Magnus Egerstedt; Haomin Zhou 001; Shui-Nee Chow (ICRA, 2014)

An inverse random source problem for the Helmholtz equation. - Gang Bao 001; Shui-Nee Chow; Peijun Li; Haomin Zhou 001 (Math. Comput., 2014)

Potential induced random teleportation on finite graphs. - Shui-Nee Chow; Xiaojing Ye; Haomin Zhou 001 (Comput. Optim. Appl., 2015)

Hyperspectral Chemical Plume Detection Algorithms Based On Multidimensional Iterative Filtering Decomposition. - Antonio Cicone; Jingfang Liu; Haomin Zhou 001 (CoRR, 2015)

Path optimization with limited sensing ability. - Sung Ha Kang; Seong Jun Kim; Haomin Zhou 001 (J. Comput. Phys., 2015)

A Multiscale Computation for Highly Oscillatory Dynamical Systems using EMPIRICAL MODE DECOMPOSITION (EMD)-type Methods. - Seong Jun Kim; Haomin Zhou 001 (Multiscale Model. Simul., 2016)

Optimal averages for nonlinear signal decompositions - Another alternative for empirical mode decomposition. - Feng Zhou 018; Lijun Yang; Haomin Zhou 001; Lihua Yang (Signal Process., 2016)

Linking Micro Event History to Macro Prediction in Point Process Models. - Yichen Wang 001; Xiaojing Ye; Haomin Zhou 001; Hongyuan Zha; Le Song (AISTATS, 2017)

Method of evolving junctions: A new approach to optimal control with constraints. - Wuchen Li; Jun Lu; Haomin Zhou 001; Shui-Nee Chow (Autom., 2017)

Method of evolving junctions: A new approach to optimal path-planning in 2D environments with moving obstacles. - Wuchen Li; Shui-Nee Chow; Magnus Egerstedt; Jun Lu; Haomin Zhou 001 (Int. J. Robotics Res., 2017)

Seafloor identification in sonar imagery via simulations of Helmholtz equations and discrete optimization. - Björn Engquist; Christina Frederick; Quyen Huynh; Haomin Zhou 001 (J. Comput. Phys., 2017)

A Weak Galerkin Finite Element Method for a Type of Fourth Order Problem Arising from Fluorescence Tomography. - Chunmei Wang; Haomin Zhou 001 (J. Sci. Comput., 2017)

Optimal Sensor Positioning; A Probability Perspective Study. - Sung Ha Kang; Seong Jun Kim; Haomin Zhou 001 (SIAM J. Sci. Comput., 2017)

Learning to Recommend via Inverse Optimal Matching. - Ruilin Li; Xiaojing Ye; Haomin Zhou 001; Hongyuan Zha (CoRR, 2018)

Influence prediction for continuous-time information propagation on networks. - Shui-Nee Chow; Xiaojing Ye; Hongyuan Zha; Haomin Zhou 001 (Networks Heterog. Media, 2018)

Parametric Fokker-Planck Equation. - Wuchen Li; Shu Liu; Hongyuan Zha; Haomin Zhou 001 (GSI, 2019)

Path Planning in Unknown Environments Using Optimal Transport Theory. - Haoyan Zhai; Magnus Egerstedt; Haomin Zhou 001 (CoRR, 2019)

EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction. - Feng Zhou 018; Haomin Zhou 001; Zhihua Yang; Lihua Yang (Expert Syst. Appl., 2019)

A 2-Stage Strategy for Non-Stationary Signal Prediction and Recovery Using Iterative Filtering and Neural Network. - Feng Zhou 018; Haomin Zhou 001; Zhihua Yang; Lihua Yang (J. Comput. Sci. Technol., 2019)

Learning to Match via Inverse Optimal Transport. - Ruilin Li; Xiaojing Ye; Haomin Zhou 001; Hongyuan Zha (J. Mach. Learn. Res., 2019)

Population Games and Discrete Optimal Transport. - Shui-Nee Chow; Wuchen Li; Jun Lu; Haomin Zhou 001 (J. Nonlinear Sci., 2019)

Learning Stochastic Behaviour of Aggregate Data. - Shaojun Ma; Shu Liu; Hongyuan Zha; Haomin Zhou 001 (CoRR, 2020)

Learning Cost Functions for Optimal Transport. - Haodong Sun; Haomin Zhou 001; Hongyuan Zha; Xiaojing Ye (CoRR, 2020)

Neural Parametric Fokker-Planck Equations. - Shu Liu; Wuchen Li; Hongyuan Zha; Haomin Zhou 001 (CoRR, 2020)

Numerical Solution of Inverse Problems by Weak Adversarial Networks. - Gang Bao 001; Xiaojing Ye; Yaohua Zang; Haomin Zhou 001 (CoRR, 2020)

Time-frequency representation of nonstationary signals: the FIFogram. - Philippe Barbe; Antonio Cicone; Wing Suet Li; Haomin Zhou 001 (CoRR, 2020)

Weak adversarial networks for high-dimensional partial differential equations. - Yaohua Zang; Gang Bao 001; Xiaojing Ye; Haomin Zhou 001 (J. Comput. Phys., 2020)

Double descent and intermittent color diffusion for landscape exploration. - Luca Dieci; Manuela Manetta; Haomin Zhou 001 (Numer. Algorithms, 2020)

Equilibrium Selection via Optimal Transport. - Shui-Nee Chow; Wuchen Li; Jun Lu; Haomin Zhou 001 (SIAM J. Appl. Math., 2020)

Learning Stochastic Behaviour from Aggregate Data. - Shaojun Ma; Shu Liu; Hongyuan Zha; Haomin Zhou 001 (ICML, 2021)

Belief Space Partitioning for Symbolic Motion Planning. - Mengxue Hou; Tony X. Lin; Haomin Zhou 001; Wei Zhang 013; Catherine R. Edwards; Fumin Zhang 001 (ICRA, 2021)

Learning High Dimensional Wasserstein Geodesics. - Shu Liu; Shaojun Ma; Yongxin Chen; Hongyuan Zha; Haomin Zhou 001 (CoRR, 2021)

Mean Field Game GAN. - Shaojun Ma; Haomin Zhou 001; Hongyuan Zha (CoRR, 2021)

Scalable Computation of Monge Maps with General Costs. - Jiaojiao Fan; Shu Liu; Shaojun Ma; Yongxin Chen; Haomin Zhou 001 (CoRR, 2021)

IF2CNN: Towards non-stationary time series feature extraction by integrating iterative filtering and convolutional neural networks. - Feng Zhou 018; Haomin Zhou 001; Zhihua Yang; Linyan Gu (Expert Syst. Appl., 2021)

Bounded Cost Path Planning for Underwater Vehicles Assisted by a Time-Invariant Partitioned Flow Field Model. - Mengxue Hou; Sungjin Cho; Haomin Zhou 001; Catherine R. Edwards; Fumin Zhang 001 (Frontiers Robotics AI, 2021)

Numerical analysis for iterative filtering with new efficient implementations based on FFT. - Antonio Cicone; Haomin Zhou 001 (Numerische Mathematik, 2021)

Method of evolving junction on optimal path planning in flows fields. - Haoyan Zhai; Mengxue Hou; Fumin Zhang 001; Haomin Zhou 001 (Auton. Robots, 2022)

New theoretical insights in the decomposition and time-frequency representation of nonstationary signals: the IMFogram algorithm. - Antonio Cicone; Wing Suet Li; Haomin Zhou 001 (CoRR, 2022)

Discrete Langevin Sampler via Wasserstein Gradient Flow. - Haoran Sun; Hanjun Dai; Bo Dai 001; Haomin Zhou 001; Dale Schuurmans (CoRR, 2022)

Path Exploration in Unknown Environments Using Fokker-Planck Equation on Graph. - Haoyan Zhai; Magnus Egerstedt; Haomin Zhou 001 (J. Intell. Robotic Syst., 2022)

Collective Motion Planning for a Group of Robots Using Intermittent Diffusion. - Christina Frederick; Magnus Egerstedt; Haomin Zhou 001 (J. Sci. Comput., 2022)

Time discretizations of Wasserstein-Hamiltonian flows. - Jianbo Cui; Luca Dieci; Haomin Zhou 001 (Math. Comput., 2022)

Neural Parametric Fokker-Planck Equation. - Shu Liu; Wuchen Li; Hongyuan Zha; Haomin Zhou 001 (SIAM J. Numer. Anal., 2022)

A Continuation Multiple Shooting Method for Wasserstein Geodesic Equation. - Jianbo Cui; Luca Dieci; Haomin Zhou 001 (SIAM J. Sci. Comput., 2022)

Discrete Langevin Samplers via Wasserstein Gradient Flow. - Haoran Sun; Hanjun Dai; Bo Dai 001; Haomin Zhou 001; Dale Schuurmans (AISTATS, 2023)

High-Dimensional Optimal Density Control with Wasserstein Metric Matching. - Shaojun Ma; Mengxue Hou; Xiaojing Ye; Haomin Zhou 001 (CDC, 2023)

Intermittent diffusion-based path planning for heterogeneous groups of mobile sensors in cluttered environments. - Christina Frederick; Haomin Zhou 001; Frank Crosby (ICRA, 2023)

Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study. - Shijun Zhang; Hongkai Zhao; Yimin Zhong; Haomin Zhou 001 (CoRR, 2023)

RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network. - Feng Zhou 018; Antonio Cicone; Haomin Zhou 001 (CoRR, 2023)

RRCNN+: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition. - Feng Zhou 018; Antonio Cicone; Haomin Zhou 001 (CoRR, 2023)

Neural Monge Map estimation and its applications. - Jiaojiao Fan; Shu Liu; Shaojun Ma; Haomin Zhou 001; Yongxin Chen (Trans. Mach. Learn. Res., 2023)

Wasserstein Hamiltonian Flow with Common Noise on Graph. - Jianbo Cui; Shu Liu; Haomin Zhou 001 (SIAM J. Appl. Math., 2023)

Optimal Control for Stochastic Nonlinear Schrödinger Equation on Graph. - Jianbo Cui; Shu Liu; Haomin Zhou 001 (SIAM J. Control. Optim., 2023)

A supervised learning scheme for computing Hamilton-Jacobi equation via density coupling. - Jianbo Cui; Shu Liu; Haomin Zhou 001 (CoRR, 2024)

Structured and Balanced Multi-component and Multi-layer Neural Networks. - Shijun Zhang; Hongkai Zhao; Yimin Zhong; Haomin Zhou 001 (CoRR, 2024)

A novel algorithm for the decomposition of non-stationary multidimensional and multivariate signals. - Roberto Cavassi; Antonio Cicone; Enza Pellegrino; Haomin Zhou 001 (CoRR, 2024)

IRCNN: A novel signal decomposition approach based on iterative residue convolutional neural network. - Feng Zhou 018; Antonio Cicone; Haomin Zhou 001 (Pattern Recognit., 2024)

Neural Control of Parametric Solutions for High-Dimensional Evolution PDEs. - Nathan Gaby; Xiaojing Ye; Haomin Zhou 001 (SIAM J. Sci. Comput., 2024)

One or two frequencies? The Iterative Filtering answers. - Antonio Cicone; Stefano Serra-Capizzano; Haomin Zhou 001 (Appl. Math. Comput., 2024)

Parameterized Wasserstein gradient flow. - Yijie Jin; Shu Liu; Hao Wu; Xiaojing Ye; Haomin Zhou 001 (J. Comput. Phys., 2025)

Parameterized Wasserstein Hamiltonian Flow. - Hao Wu; Shu Liu; Xiaojing Ye; Haomin Zhou 001 (SIAM J. Numer. Anal., 2025)

Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential. - Shijun Zhang; Hongkai Zhao; Yimin Zhong; Haomin Zhou 001 (CoRR, 2025)

A parameterized Wasserstein Hamiltonian flow approach for solving the Schrödinger equation. - Hao Wu; Shu Liu; Xiaojing Ye; Haomin Zhou 001 (CoRR, 2025)

Identification of Differential Equations by Dynamics-Guided Weighted Weak Form with Voting. - Jiahui Cheng; Sung Ha Kang; Haomin Zhou 001; Wenjing Liao (CoRR, 2025)