|
Publications & Preprints
Preprints
CryoTRANS: Quality Preserved Trajectory for Boosting Resolutions of Rare Conformations in cryo-EM
Xiao Fan, Qi Zhang, Mingxu Hu, Hui Zhang, Jianying Zhu, Zuoqiang Shi, Chenglong Bao. Preprint. [pdf]
Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
Chenglong Bao, Liang Chen, Jiahong Li, Zuowei Shen. ArXiv:2401.07672. [pdf]
Addressing Preferred Orientation in Single-Particle cryo-EM through AI-generated Auxiliary Particles
Hui Zhang, Dihan Zheng, Qiurong Wu, Nieng Yan, Zuoqiang Shi, Mingxu Hu, Chenglong Bao. ArXiv:2309.14954. [pdf]
Riemannian Anderson Mixing Methods for Minimizing C2-Functions on Riemannian Manifolds
Zanyu Li, Chenglong Bao. ArXiv:2309.04091. [pdf]
The Global R-linear Convergence of Nesterov’s Accelerated Gradient Method with Unknown Strongly Convex Parameter
Chenglong Bao, Liang Chen, Jiahong Li. ArXiv:2308.14080. [pdf]
An Axiomatized PDE Model of Deep Neural Networks
Tangjun Wang, Wenqi Tao, Chenglong Bao, Zuoqiang Shi. ArXiv:2307.12333. [pdf]
Convergence Analysis for Restarted Anderson Mixing and Beyond
Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. ArXiv:2307.02062. [pdf]
The Moments of Orientation Estimations Considering Molecular Symmetry in Cryo-EM
Qi Zhang, Chenglong Bao, Hai Lin, Mingxu Hu. ArXiv:2301.05426. [pdf][Code]
Semi-Supervised Clustering via Dynamic Graph Structure Learning
Huaming Ling, Chenglong Bao, Xin Liang, Zuoqiang Shi. ArXiv:2209.02513. [pdf]
On the robust isolated calmness of a class of nonsmooth optimizations on Riemannian manifolds and its applications
Yuexin Zhou, Chenglong Bao, Chao Ding. ArXiv:2208.07518. [pdf]
Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection
Ruichen Jiang, Ya-Feng Liu, Chenglong Bao, Bo Jiang. Arxiv:2102.04586. [pdf]
Journal papers
Enhancing Density Maps by Removing the Majority of Particles in Single Particle Cryogenic Electron Microscopy Final Stacks
Mengjia Cai, Jianying Zhu, Qi Zhang, Yu Xu, Zuoqiang Shi, Chenglong Bao, Mingxu Hu. Journal of Visualized Experiments, accepted. 2024.
PhaseNet: A Deep Learning Based Phase Reconstruction Method for Ground-based Astronomy
Dihan Zheng, Shiqi Tang, Roland Wagner, Ronny Ramlau, Chenglong Bao, Raymond Chan. SIAM Journal on Imaging Sciences, accepted. 2024.
Convergence Analysis for Bregman Iterations in Minimizing a Class of Landau Free Energy Functionals
Chenglong Bao, Chang Chen, Kai Jiang, Lingyun Qiu. SIAM Journal on Numerical Analysis.62(1), 476-499, 2024.[pdf]
Diffusion Mechanism in Neural Network: Theory and Applications
Tangjun Wang, Zehao Dou, Chenglong Bao, Zuoqiang Shi. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(2), 667-680, 2024[pdf]
A Minority of Final Stacks Yields
Superior Amplitude in Single-Particle cryo-EM
Jianying Zhu, Qi Zhang, Hui Zhang, Zuoqiang Shi, Mingxu Hu, Chenglong Bao. Nature Communications. 14(7822), 2023.[pdf][Code][The Top 25 Physics Articles of 2023 in Nature Communications]
Robust Full Waveform Inversion: A Source Wavelet Manipulation Perspective
Chenglong Bao, Lingyun Qiu, Rongqian Wang. SIAM Journal on Scientific Computing. 45(6), B753-B775, 2023. [pdf][Code]
Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods
Jintao Xu, Chenglong Bao, Wenxun Xing. Optimization Letters. 2023.[pdf]
A Scalable Deep Learning Approach for Solving High-dimensional Dynamic Optimal Transport
Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang Shi. SIAM Journal on Scientific Computing, 45(4), B544-B563, 2023 [pdf]
Approximation Analysis of Convolutional Neural Networks
Chenglong Bao, Qianxiao Li, Zuowei Shen, Cheng Tai, Lei Wu, Xueshuang Xiang. East Asian Journal on Applied Mathematics, 13(3), 524-549, 2023. [pdf]
Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach
Dihan Zheng, Xiaowen Zhang, Kaisheng Ma, Chenglong Bao. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(5), 5889-5903, 2023. [pdf][Code]
A Semismooth Newton based Augmented Lagrangian Method for Nonsmooth Optimization on Matrix Manifolds
Yuhao Zhou, Chenglong Bao, Chao Ding, Jun Zhu, Mathematical Programming, 201, 1-61, 2023. [pdf][Code]
Unsupervised Deep Learning Meets Chan-Vese Model
Dihan Zheng, Chenglong Bao, Zuoqiang Shi, Haibin Ling, Kaisheng Ma. CSIAM Transactions on Applied Mathematics, 3(4), 662-691.2022. [pdf][Code]
Self-Distillation: Towards Efficient and Compact Neural Networks
Linfeng Zhang, Chenglong Bao, Kaisheng Ma. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8), 4388-4403 2022. [pdf]
Adapting the Residual Dense Network for Seismic Data Denoising and Upscaling
Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, Dinghui Yang. Geophysics, 87(4), V321-V340, 2022. [pdf]
Improved Harmonic Incompatibility Removal for Susceptibility Mapping via Reduction of Basis Mismatch
Chenglong Bao, Jian-Feng Cai, Jae Kyu Choi, Bin Dong, Ke Wei. Journal of Computational Mathematics, 40(6), 914–937, 2022. [pdf]
An adaptive block Bregman proximal gradient method for computing stationary states of multicomponent phase-field crystal model
Chenglong Bao, Chang Chen, Kai Jiang. CSIAM Transactions on Applied Mathematics, 3(1), 133-171, 2022. [pdf]
Zero Norm based Analysis Model for Image Smoothing and Reconstruction
Jiebo Song, Jia Li, Zhengan Yao, Kaisheng Ma, Chenglong Bao. Inverse Problems, 36(11), 2020. [pdf]
Efficient Numerical Methods for Computing the Stationary States of Phase Field Crystal Models
Kai Jiang, Wei Si, Chang Chen, Chenglong Bao. SIAM Journal on Scientific Computing, 42(6), B1350–B1377, 2020. [pdf]
Barzilai-Borwein-based adaptive learning rate for deep learning
Jinxiu Liang, Yong Xu, Chenglong Bao, Yuhui Quan, Hui Ji. Pattern Recognition Letters , 128(1), 197-203, 2019. [pdf]
Whole brain susceptibility mapping using harmonic incompatibility removal
Chenglong Bao, Jae Kyu Choi, and Bin Dong. SIAM Journal on Imaging Science,12(1), 492-520,2019. [pdf]
Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints: the example from a molti-domain protein Pub 1
Guanhua Zhu, Wei Liu, Chenglong Bao, Dudu Tong, Hui Ji, Zuowei Shen, Daiwei Yang, and Lanyuan Lu. Proteins: Structure, Function, and Bioinformatics, 86 (5), 501–514, 2018.[pdf]
PET-MRI joint reconstruction by joint sparsity based tight frame regolarization
Jae Kyu Choi, Chenglong Bao, and Xiaoqun Zhang. SIAM Journal on Imaging Sciences, 11 (2), 1179–1204, 2018. [pdf]
Coherence retrieval using trace regolarization
Chenglong Bao, George Barbastathis, Hui Ji, Zuowei Shen, and Zhengyun Zhang. SIAM Journal on Imaging Sciences, 11 (1), 679–706, 2018. [pdf]
Apparent coherence loss in phase space tomography
Zhengyun Zhang, Chenglong Bao, Hui Ji, Zuowei Shen, and George Barbastathis. Journal of the Optical Society of America A, 34 (11), 2025–2033, 2017.[pdf]
Image restoration by minimizing zero norm of wavelet frame coefficients
Chenglong Bao, Bin Dong, Likun Hou, Zuowei Shen, Xiaoqun Zhang, and Xue Zhang. Inverse Problems, 32 (1), 2016. [pdf]
Cerebellar functional parcellation using sparse dictionary learning clustering
Changqing Wang, Judy Kipping, Chenglong Bao, Hui Ji, and Anqi Qiu. Frontiers in Neuroscience, 10 (188), 2016 [pdf]
Dictionary learning for sparse coding: algorithms and convergence analysis
Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (7), 1356–1369, 2016. [pdf][Code]
Convergence analysis for iterative data-driven tight frame construction scheme
Chenglong Bao, Hui Ji, and Zuowei Shen. Applied and Computational Harmonic Analysis, 38 (3), 510–523, 2015. [pdf]
Conference papers
SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
Dihan Zheng, Yihang Zou, Xiaowen Zhang, Chenglong Bao. CVPR, 2024.
A Variant of Anderson Mixing with Minimal Memory Size
Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. NeurIPS, 2022.[pdf]
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications
Fuchao Wei, Chenglong Bao, Yang Liu. ICLR, 2022. [pdf]
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
Fuchao Wei, Chenglong Bao, Yang Liu. NeurIPS, 2021. [pdf][Code]
AFEC: Active Forgetting of Negative Transfer in Continual Learning
Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, Kaisheng Ma, Jun Zhu, Yi Zhong. NeurIPS, 2021. [pdf] Seismic Data Denoising and Interpolation Using Deep Learning
Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, Dinghui Yang. EAGE Annual Conference and Exhibition, 2021. [pdf]
Seismic Waveform Inversion with Source Manipulation
Rongqian Wang, Chenglong Bao, Lingyun Qiu. EAGE Annual Conference and Exhibition, 2021. [pdf]
Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks
Linfeng Zhang, Xiaoman Zhang, Chenglong Bao, Kaisheng Ma. IJCNN, 2021. [pdf]
An Unsupervised Deep Learning Approach for Real-World Image Denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. ICLR, 2021. [pdf] [Code]
Task-Orientated Feature Distillation
Linfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. NeurIPS 2020. [pdf][Code]
Interpolation between Residual and Non-Residual Networks
Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi. ICML 2020. [pdf][Code]
Auxiliary Training: Towards Accurate and Robust Models
Linfeng Zhang, Muzhou Yu, Tong Chen, Zuoqiang Shi, Chenglong Bao, Kaisheng Ma. CVPR 2020. [pdf][Code]
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Sia huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, Kaisheng Ma. CVPR 2020. [pdf]
Robust Document Distance with Wasserstein-Fisher-Rao Metric
Zihao Wang, Datong Zhou, Yong Zhang, Chenglong Bao, Hao Wu. ACML 2020. [pdf]
SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models
Linfeng Zhang, Zhanhong Tan, Jiebo Song, Jingwei Chen, Chenglong Bao, and Kaisheng Ma. NeurIPS. Vancouver, 2019. [pdf][Code]
Be your own teacher: improve the performance of convolutional neural networks via self distillation
Linfeng Zhang, Jiebo Song, Anni Gao, Jingwei Chen, Chenglong Bao, and Kaisheng Ma. ICCV, Seoul, 2019. [pdf][Code]
Equiangular kernel dictionary learning with applications to dynamic texture analysis
Yuhui Quan, Chenglong Bao, and Hui Ji. CVPR, Las Vegas, 2016 [pdf]
A convergent incoherent dictionary learning algorithm for sparse coding
Chenglong Bao, Yuhui Quan, and Hui Ji. ECCV, Zurich, 2014. [pdf]
L0 norm based dictionary learning by proximal methods with global convergence
Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen. CVPR, Columbus, 2014. [pdf]
Fast sparsity based orthogonal dictionary learning for image restoration
Chenglong Bao, Jian-feng Cai, and Hui Ji. ICCV, Sydney,2013. [pdf]
Real time robust L1 tracker using accelerated proximal gradient method
Chenglong Bao, Yi Wu, Haibin Ling, and Hui Ji. CVPR, Rhole Island, 2012. [pdf]
Unpublsihed Technical Reports
An efficient method for computing stationary states of phase field crystal models
Kai Jiang, Wei Si, Chenglong Bao. Arxiv:1909.00305. [pdf]
Brain-inspired reverse adversarial examples
Shaokai Ye, Sia Huat Tan, Kaidi Xu, Yanzhi Wang, Chenglong Bao, and Kaisheng Ma. arXiv:1905.12171. [pdf]
|