Low dimensional manifold model in hyperspectral image reconstruction. - Zuoqiang Shi; Wei Zhu 007; Stanley J. Osher (CoRR, 2016)

Pre-processing and classification of hyperspectral imagery via selective inpainting. - Victoria Chayes; Kevin Miller; Rasika Bhalerao; Jiajie Luo; Wei Zhu 007; Andrea L. Bertozzi; Wenzhi Liao; Stanley J. Osher (ICASSP, 2017)

Weighted Nonlocal Laplacian on Interpolation from Sparse Data. - Zuoqiang Shi; Stanley J. Osher; Wei Zhu 007 (J. Sci. Comput., 2017)

Low Dimensional Manifold Model for Image Processing. - Stanley J. Osher; Zuoqiang Shi; Wei Zhu 007 (SIAM J. Imaging Sci., 2017)

Unsupervised Classification in Hyperspectral Imagery With Nonlocal Total Variation and Primal-Dual Hybrid Gradient Algorithm. - Wei Zhu 007; Victoria Chayes; Alexandre Tiard; Stephanie Sánchez; Devin Dahlberg; Andrea L. Bertozzi; Stanley J. Osher; Dominique Zosso; Da Kuang (IEEE Trans. Geosci. Remote. Sens., 2017)

Nonlocal Variational Methods in Image and Data Processing. - Wei Zhu 007 (2017)

LDMNet: Low Dimensional Manifold Regularized Neural Networks. - Wei Zhu 007; Qiang Qiu 001; Jiaji Huang; A. Robert Calderbank; Guillermo Sapiro; Ingrid Daubechies (CVPR, 2018)

Deep Neural Nets with Interpolating Function as Output Activation. - Bao Wang 001; Xiyang Luo; Zhen Li 029; Wei Zhu 007; Zuoqiang Shi; Stanley J. Osher (NeurIPS, 2018)

Scalable Low Dimensional Manifold Model In The Reconstruction Of Noisy And Incomplete Hyperspectral Images. - Wei Zhu 007; Zuoqiang Shi; Stanley J. Osher (WHISPERS, 2018)

Deep Learning with Data Dependent Implicit Activation Function. - Bao Wang 001; Xiyang Luo; Zhen Li 029; Wei Zhu 007; Zuoqiang Shi; Stanley J. Osher (CoRR, 2018)

Adversarial Defense via Data Dependent Activation Function and Total Variation Minimization. - Bao Wang 001; Alex Tong Lin; Zuoqiang Shi; Wei Zhu 007; Penghang Yin; Andrea L. Bertozzi; Stanley J. Osher (CoRR, 2018)

Scientific data interpolation with low dimensional manifold model. - Wei Zhu 007; Bao Wang 001; Richard C. Barnard; Cory D. Hauck; Frank Jenko; Stanley J. Osher (J. Comput. Phys., 2018)

Generalization of the Weighted Nonlocal Laplacian in Low Dimensional Manifold Model. - Zuoqiang Shi; Stanley J. Osher; Wei Zhu 007 (J. Sci. Comput., 2018)

Scale-Equivariant Neural Networks with Decomposed Convolutional Filters. - Wei Zhu 007; Qiang Qiu 001; A. Robert Calderbank; Guillermo Sapiro; Xiuyuan Cheng (CoRR, 2019)

Constructing curvelet-like bases and low-redundancy frames. - Wei Zhu 007; Ingrid Daubechies (CoRR, 2019)

Stop Memorizing: A Data-Dependent Regularization Framework for Intrinsic Pattern Learning. - Wei Zhu 007; Qiang Qiu 001; Bao Wang 001; Jianfeng Lu 001; Guillermo Sapiro; Ingrid Daubechies (SIAM J. Math. Data Sci., 2019)

Hyperspectral Anomaly Detection via Global and Local Joint Modeling of Background. - Zebin Wu 001; Wei Zhu 007; Jocelyn Chanussot; Yang Xu 006; Stanley J. Osher (IEEE Trans. Signal Process., 2019)

Structure-preserving GANs. - Jeremiah Birrell; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (ICML, 2022)

Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters. - Wei Zhu 007; Qiang Qiu 001; A. Robert Calderbank; Guillermo Sapiro; Xiuyuan Cheng (J. Mach. Learn. Res., 2022)

Sample Complexity of Probability Divergences under Group Symmetry. - Ziyu Chen; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (ICML, 2023)

Learning heavy-tailed distributions with Wasserstein-proximal-regularized α-divergences. - Ziyu Chen; Hyemin Gu; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (CoRR, 2024)

Nonlinear denoising score matching for enhanced learning of structured distributions. - Jeremiah Birrell; Markos A. Katsoulakis; Luc Rey-Bellet; Benjamin J. Zhang; Wei Zhu 007 (CoRR, 2024)

Statistical Guarantees of Group-Invariant GANs. - Ziyu Chen; Markos A. Katsoulakis; Luc Rey-Bellet; Wei Zhu 007 (SIAM/ASA J. Uncertain. Quantification, 2025)