Publications & Preprints

Preprints

1. On the Convergence Analysis of an Inexact Preconditioned Stochastic Model-Based Algorithm
   Chenglong Bao, Yancheng Yuan, Shulan Zhu ArXiv:2512.10826. [pdf]

2. Well-Posedness and Efficient Algorithms for Inverse Optimal Transport with Bregman Regularization
   Chenglong Bao, Zanyu Li, Yunan Yang ArXiv:2510.03803. [pdf]

3. A Stochastic Gradient Descent Method with Global Convergence for Minimizing Nearly Convex Functions
   Chenglong Bao, Liang Chen, Weizhi Shao ArXiv:2505.03222. [pdf]

4. Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
   Chenglong Bao, Liang Chen, Jiahong Li, Zuowei Shen. ArXiv:2401.07672. [pdf]

5. Convergence Analysis for Restarted Anderson Mixing and Beyond
   Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. ArXiv:2307.02062. [pdf]

Selected journal papers

1. On the robust isolated calmness of a class of nonsmooth optimizations on Riemannian manifolds and its applications
   Chenglong Bao, Chao Ding, Yuexin Zhou. Computational Optimization and Applications. 2025 [pdf]

2. CryoPROS: Correcting Misalignment Caused by Preferred Orientation Using AI-generated Auxiliary Particles
   Hui Zhang, Dihan Zheng, Qiurong Wu, Nieng Yan, Han Peng, Qi Hu, Ying Peng, Zhaofeng Yan, Zuoqiang Shi, Chenglong Bao, Mingxu Hu. Nature Communications. 16(4565), 2025 [pdf][Code & Demo]

3. Convection-Diffusion Equation: A Theoretically Certified Framework for Neural Networks
   Tangjun Wang, Chenglong Bao, Zuoqiang Shi. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(5), 4170-4182, 2025 [pdf]

4. Riemannian Anderson Mixing Methods for Minimizing C2-Functions on Riemannian Manifolds
   Zanyu Li, Chenglong Bao. Mathematics of Operations Research. 2025 [pdf (online version)]

5. CryoTRANS: Predicting High-resolution Maps of Rare Conformations from Self-supervised Trajectories in Cryo-EM
   Xiao Fan, Qi Zhang, Hui Zhang, Jianying Zhu, Lili Ju, Zuoqiang Shi, Mingxu Hu, Chenglong Bao. Communications Biology. 7(1058), 2024. [pdf][Code][Demo]

6. Averaging Orientations with Molecular Symmetry in Cryo-EM
   Qi Zhang, Chenglong Bao, Hai Lin, Mingxu Hu. SIAM Journal on Imaging Sciences. 17(4), 2714-2195, 2024. [pdf][Code & Demo]

7. 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. 207, 2024. [pdf] [Video]

8. 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]

9. 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]

10. 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 & Demo][The Top 25 Physics Articles of 2023 in Nature Communications]

11. 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 & Demo]

12. 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]

13. 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]

14. 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]

15. 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]

16. 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]

17. 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]

18. 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]

19. 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]

20. 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]

21. 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]

22. 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]

23. 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]

24. 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] (Editors' Pick)

25. 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]

26. 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]

27. 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]

Selected Conference papers

1. A Regularized Newton Method for Nonconvex Optimization with Global and Local Complexity Guarantees
   Yuhao Zhou, Jintao Xu, Chenglong Bao, Chao Ding, Jun Zhu. NeurIPS, 2025. [pdf][Code & Demo]

2. A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
   Shulan Zhu, Chenglong Bao, Defeng Sun, Yancheng Yuan. ICLR, 2025.

3. SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder
   Dihan Zheng, Yihang Zou, Xiaowen Zhang, Chenglong Bao. CVPR, 2024. [pdf][Code]

4. A Variant of Anderson Mixing with Minimal Memory Size
   Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang. NeurIPS, 2022.[pdf]

5. A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications
   Fuchao Wei, Chenglong Bao, Yang Liu. ICLR, 2022. [pdf]

6. Stochastic Anderson Mixing for Nonconvex Stochastic Optimization
   Fuchao Wei, Chenglong Bao, Yang Liu. NeurIPS, 2021. [pdf][Code]

7. 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]

8. Task-Orientated Feature Distillation
   Linfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, Chenglong Bao. NeurIPS 2020. [pdf][Code]

9. Interpolation between Residual and Non-Residual Networks
   Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi. ICML 2020. [pdf][Code]

10. Auxiliary Training: Towards Accurate and Robust Models
    Linfeng Zhang, Muzhou Yu, Tong Chen, Zuoqiang Shi, Chenglong Bao, Kaisheng Ma. CVPR 2020. [pdf][Code]

11. 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]

12. 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]

13. A convergent incoherent dictionary learning algorithm for sparse coding
    Chenglong Bao, Yuhui Quan, and Hui Ji. ECCV, Zurich, 2014. [pdf]

14. L0 norm based dictionary learning by proximal methods with global convergence
    Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen. CVPR, Columbus, 2014. [pdf]

15. Fast sparsity based orthogonal dictionary learning for image restoration
    Chenglong Bao, Jian-feng Cai, and Hui Ji. ICCV, Sydney,2013. [pdf]

16. 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

1. 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]

2. Tightness and Equivalence of Semidefinite Relaxations for MIMO Detection
   Ruichen Jiang, Ya-Feng Liu, Chenglong Bao, Bo Jiang. Arxiv:2102.04586. [pdf]

3. An efficient method for computing stationary states of phase field crystal models
   Kai Jiang, Wei Si, Chenglong Bao. Arxiv:1909.00305. [pdf]

4. Brain-inspired reverse adversarial examples
   Shaokai Ye, Sia Huat Tan, Kaidi Xu, Yanzhi Wang, Chenglong Bao, and Kaisheng Ma. arXiv:1905.12171. [pdf]