BIMSA > Chenglong Bao
Assistant Professor Chenglong Bao

Affiliation: BIMSA , YMSC

Group: Computational Mathematics

Email: clbao@tsinghua.edu.cn

Research Field: Data Sciences and Applied Matheamtics

Webpage: https://matbc.github.io

Education Experience

  • 2009 - 2014      National University of Singapore      Matheamtics      Ph.D      (Supervisor: Prof. Hui Ji and Prof. Defeng Sun)
  • 2005 - 2009      Sun Yat-Sen University      Mathematics      Bachelor

Work Experience

  • 2021 -      BIMSA      Adjunct Assistant Professor
  • 2018 -      Yau Mathematical Sciences Center      Assistant Professor
  • 2015 - 2017      National University of Singapore      Research Fellow

Publication

  • [1] Dihan Zheng, Yihang Zou, Xiaowen Zhang, and Chenglong Bao, SeNM-VAE: Semi-Supervised Noise Modeling with Hierarchical Variational Autoencoder, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle WA, USA, June 17-21, 2024(2024), 25889-25899
  • [2] Xiao Fan, Qi Zhang, Mingxu Hu, Hui Zhang, Jianying Zhu, Zuoqiang Shi, and Chenglong Bao, CryoTRANS: Quality Preserved Trajectory for Boosting Resolutions of Rare Conformations in cryo-EM, Preprint(2024)
  • [3] Tangjun Wang, Zehao Dou, Chenglong Bao, and Zuoqiang Shi, Diffusion Mechanism in Residual Neural Network: Theory and Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(2024), 2, 667-680
  • [4] Chenglong Bao, Liang Chen, Jiahong Li, Zuowei Shen, Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence(2024)
  • [5] Chenglong Bao; Chang Chen; Kai Jiang; Lingyun Qiu, Convergence analysis for Bregman iterations in minimizing a class of Landau free energy functionals, SIAM Journal on Numerical Analysis, 62(2024), 1, 476-499
  • [6] Dihan Zheng, Shiqi Tang, Roland Wagner, Ronny Ramlau, Chenglong Bao, and Raymond H. Chan, PhaseNet: A Deep Learning Based Phase Reconstruction Method for Ground-Based Astronomy, SIAM Journal on Imaging Sciences, 17(2024), 3
  • [7] Jianying Zhu, Qi Zhang, Hui Zhang, Zuoqiang Shi, Mingxu Hu, Chenglong Bao, A minority of final stacks yields superior amplitude in single-particle cryo-EM, Nature Communications, 7822(2023), 14
  • [8] Zanyu Li, Chenglong Bao, Riemannian Anderson Mixing Methods for Minimizing C2-Functions on Riemannian Manifolds(2023)
  • [9] Hui Zhang, Dihan Zheng, Qiurong Wu, Nieng Yan, Zuoqiang Shi, Mingxu Hu, and Chenglong Bao, Addressing Preferred Orientation in Single-Particle cryo-EM through AI-generated Auxiliary Particles(2023)
  • [10] Chenglong Bao, Liang Chen, Jiahong Li., The Global R-linear Convergence of Nesterov’s Accelerated Gradient Method with Unknown Strongly Convex Parameter(2023)
  • [11] Convergence Analysis for Restarted Anderson Mixing and Beyond, Fuchao Wei, Chenglong Bao, Yang Liu, Guangwen Yang.(2023)
  • [12] Jintao Xu, Chenglong Bao, and Wenxun Xing, Convergence Rates of Training Deep Neural Networks via Alternating Minimization Methods, Optimization Letters, 18(2023), 4, 909-923
  • [13] Dihan Zheng, Xiaowen Zhang, Kaisheng Ma, and Chenglong Bao, Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2023), 5, 5889-5903
  • [14] Chenglong Bao, Qianxiao Li, Zuowei Shen, Cheng Tai, Lei Wu, and Xueshuang Xiang, Approximation Analysis of Convolutional Neural Networks, East Asian Journal on Applied Mathematics, 13(3)(2023), 524-549
  • [15] Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, and Zuoqiang Shi, A Scalable Deep Learning Approach for Solving High-dimensional Dynamic Optimal Transport, SIAM Journal on Scientific Computing, 45(2023), 4, B544-B563
  • [16] Chenglong Bao, Lingyun Qiu, and Rongqian Wang, Robust Full Waveform Inversion: A Source Wavelet Manipulation Perspective, SIAM Journal on Scientific Computing, 45(2023), 6, B753-B775
  • [17] Qi Zhang, Chenglong Bao, Hai Lin, Mingxu Hu, Averaging Orientations with Molecular Symmetry in Cryo-EM, accepted by SIAM Journal on Imaging Sciences(2023)
  • [18] Yuhao Zhou, Chenglong Bao, Chao Ding, Jun Zhu, A Semismooth Newton based Augmented Lagrangian Method for Nonsmooth Optimization on Matrix Manifolds, Mathematical Programming, 201(2023), 1-61
  • [19] Linfeng Zhang, Chenglong Bao, and Kaisheng Ma, Self-Distillation: Towards Efficient and Compact Neural Networks, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(8)(2022), 4388-4403
  • [20] 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.
  • [21] Yuexin Zhou, Chenglong Bao, Chao Ding, On the robust isolated calmness of a class of nonsmooth optimizations on Riemannian manifolds and its applications(2022)
  • [22] Dihan Zheng, Chenglong Bao, Zuoqiang Shi, Haibin Ling, and Kaisheng Ma, Unsupervised Deep Learning Meets Chan-Vese Model, CSIAM Transactions on Applied Mathematics, 3(2022), 4, 662-691
  • [23] Fuchao Wei, Chenglong Bao, Yang Liu, and Guangwen Yang, A Variant of Anderson Mixing with Minimal Memory Size, Advances in Neural Information Processing Systems, 35(2022), 16650-16663
  • [24] Fuchao Wei, Chenglong Bao, and Yang Liu, A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications, The Tenth International Conference on Learning Representations (ICLR), Virtual Event(2022)
  • [25] Huaming Ling, Chenglong Bao, Xin Liang, Zuoqiang Shi, Semi-Supervised Clustering via Dynamic Graph Structure Learning, arXiv:2209.02513(2022)
  • [26] Chenglong Bao, Chang Chen, Kai Jiang, An adaptive block Bregman proximal gradient method for computing stationary states of multicomponent phase-field crystal model, CSIAM Transactions on Applied Mathematics, 3(1)(2022), 133-171
  • [27] Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, and Dinghui Yang, Adapting the Residual Dense Network for Seismic Data Denoising and Upscaling, Geophysics, 87(4)(2022), V321-V340
  • [28] Chenglong Bao, Jian-Feng Cai, Jae Kyu Choi, Bin Dong, Ke Wei, Improved Harmonic Incompatibility Removal for Susceptibility Mapping via Reduction of Basis Mismatch, Journal of Computational Mathematics, 40(6)(2022), 914-937
  • [29] Rongqian Wang, Chenglong Bao, and Lingyun Qiu, Seismic Waveform Inversion with Source Manipulation, The 82nd EAGE Annual Conference & Exhibition(2021), 1-5
  • [30] Rongqian Wang, Ruixuan Zhang, Chenglong Bao, Lingyun Qiu, and Dinghui Yang, Seismic Data Denoising and Interpolation Using Deep Learning, The 82nd EAGE Annual Conference & Exhibition(2021), 1-5
  • [31] Linfeng Zhang, Xiaoman Zhang, Chenglong Bao, and Kaisheng Ma, Wavelet J-Net: A Frequency Perspective on Convolutional Neural Networks, 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China(2021), 1-8
  • [32] Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, and Chenglong Bao, An unsupervised deep learning approach for real-world image denoising, The Nineth International Conference on Learning Representations (ICLR), Virtual Event, May 3-7, 2021(2021)
  • [33] Liyuan Wang, Mingtian Zhang, Zhongfan Jia, Qian Li, Chenglong Bao, and Kaisheng Ma, Afec: Active forgetting of negative transfer in continual learning, Advances in Neural Information Processing Systems, 34(2021), 22379-22391
  • [34] Fuchao Wei, Chenglong Bao, and Yang Liu, Stochastic Anderson Mixing for Nonconvex Stochastic Optimization, Advances in Neural Information Processing Systems, 34(2021), 22995-23008
  • [35] Jiebo Song, Jia Li, Zhengan Yao, Kaisheng Ma, Chenglong Bao, Zero Norm based Analysis Model for Image Smoothing and Reconstruction, Inverse Problems, 36(2020), 11
  • [36] Kai Jiang, Wei Si, Chang Chen, Chenglong Bao, Efficient Numerical Methods for Computing the Stationary States of Phase Field Crystal Models, SIAM Journal on Scientific Computing, 42(2020), 6, B1350-B1357
  • [37] Zonghan Yang, Yang Liu, Chenglong Bao, and Zuoqiang Shi, Interpolation between Residual and Non-Residual Networks, Proceedings of Machine Learning Research, 119(2020), 10736-10745
  • [38] Shaokai Ye, Kailu Wu, Mu Zhou, Yunfei Yang, Sia Huat Tan, Kaidi Xu, Jiebo Song, Chenglong Bao, and Kaisheng Ma, Light-weight calibrator: a separable component for unsupervised domain adaptation, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 2020(2020), 13736-13745
  • [39] Linfeng Zhang, Yukang Shi, Zuoqiang Shi, Kaisheng Ma, and Chenglong Bao, Task-Oriented Feature Distillation, Advances in Neural Information Processing Systems, 33(2020), 14759-14771
  • [40] Jinxiu Liang, Yong Xu, Chenglong Bao, Yuhui Quan, and Hui Ji, Barzilai–Borwein-based adaptive learning rate for deep learning, Pattern Recognition Letters, 128(2019), 197-203
  • [41] Linfeng Zhang, Jiebo Song, Anni Gao, Jingwei Chen, Chenglong Bao, and Kaisheng Ma, Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation, 2019 IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Korea (South), 2019(2019), 3713-3722
  • [42] Linfeng Zhang, Zhanhong Tan, Jiebo Song, Jingwei Chen, Chenglong Bao, and Kaisheng Ma, SCAN: A Scalable Neural Networks Framework Towards Compact and Efficient Models, Advances in Neural Information Processing Systems, 32(2019), 4027-4036
  • [43] Chenglong Bao, George Barbastathis, Hui Ji, Zuowei Shen, and Zhengyun Zhang, Coherence Retrieval Using Trace Regularization, SIAM J. IMAGING SCIENCES, 11(2018), 1, 679-706
  • [44] Chenglong Bao, Hui Ji, Yuhui Quan, and Zuowei Shen, Dictionary Learning for Sparse Coding: Algorithms and Convergence Analysis, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 38(2016), 7
  • [45] Chenglong Bao, Hui Ji, Zuowei Shen, Convergence analysis for iterative data-driven tight frame construction scheme, Appl. Comput. Harmon. Anal., 38(2015), 510-523

 

Update Time: 2024-09-12 17:18:05