Bin Dong(董彬) Long CV, Short CV
Professor
Beijing International Center for Mathematical
Research (BICMR),
Center for Machine Learning Research (CMLR)
Office: BICMR,77101; Phone:
+8610-62744091
Email: dongbin {at} math {dot} pku {dot} edu {dot} cn
===============================================================================================
About -- Biography -- Events -- Publications
-- Teaching
===============================================================================================
Preprints
1. Guoxiong Gao, Haocheng Ju, Jiedong Jiang, Zihan Qin, Bin
Dong, A semantic search engine for
mathlib4, arXiv:2403.13310.
2. Bin Dong,
Ting Lin, Zuowei Shen, Peichu
Xie, Analysis
of a wavelet frame based two-scale model for enhanced edges,
arXiv:2401.02688.
3. Xinyu Xiao, Zhennan Zhou, Bin
Dong, Dingjiong Ma, Li Zhou, Jie
Sun, Meta-DSP: A Meta-Learning
Approach for Data-Driven Nonlinear Compensation in High-Speed Optical Fiber
Systems, arXiv:2311.10416.
4. Mingze Yuan, Peng Bao, Jiajia
Yuan, Yunhao Shen, Zifan
Chen, Yi Xie, Jie Zhao,
Yang Chen, Li Zhang, Lin Shen, Bin Dong, Large Language Models Illuminate a
Progressive Pathway to Artificial Healthcare Assistant: A Review, arXiv:2311.01918.
5. Zhanhong Ye, Hongsheng Liu, Zidong Wang, Bin Dong, Analysis of the Decoder Width for
Parametric Partial Differential Equations, arXiv:2306.14390.
6. Zifan Chen, Jiazheng Li, Jie Zhao, Yiting Liu, Hongfeng Li, Bin
Dong, Lei Tang and Li Zhang, PropNet:
Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans,
arXiv:2305.17871.
7. Peng Bao,
Gong Wang, Ruijie Yang, Bin Dong, Deep Reinforcement Learning for Beam
Angle Optimization of Intensity-Modulated Radiation Therapy,
arXiv:2303.03812.
8. Haocheng Ju, Haimiao Zhang, Lin
Li, Xiao Li, Bin Dong, A Comparative
Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation
and Signal Detection, arXiv:2303.03678.
9. Pu Yang and
Bin Dong, L2SR: Learning to Sample
and Reconstruct for Accelerated MRI, arXiv:2212.02190.
Published
AI for Mathematics
1.
Bin Dong, Xuhua He, Pengfei Jin, Felix Schremmer, Qingchao Yu, Machine learning assisted exploration
for affine Deligne-Lusztig varieties, accepted by Peking Mathematical
Journal, 2024 (arXiv:2308.11355).
Machine Learning
and Scientific Computing
1.
Zhuoyuan Li, Bin
Dong, Pingwen Zhang, Latent assimilation with implicit
neural representations for unknown dynamics, Journal of Computational
Physics, doi.org/10.1016/j.jcp.2024.112953, 2024 (arXiv:2309.09574).
2.
Zhanhong Ye, Xiang
Huang, Leheng Chen, Hongsheng
Liu, Zidong Wang, Bin Dong, PDEformer: Towards a Foundation Model
for One-Dimensional Partial Differential Equations, ICLR 2024 Workshop on
AI4DifferentialEquations In Science (arXiv:2402.12652).
3.
Yifan Luo, Yiming Tang, Chengfeng Shen, Zhennan Zhou, Bin Dong, Prompt engineering through the lens of
optimal control, Journal of Machine Learning, 2, 241-258, 2023
(arXiv:2310.14201).
4.
Zhengyi Li, Yanli Wang, Hongsheng Liu, Zidong Wang, Bin
Dong, Solving Boltzmann equation
with neural sparse representation, SIAM Journal on Scientific Computing, 46(2),
C186--C215, 2023 (arXiv:2302.09233).
5.
Zhanhong Ye, Xiang
Huang, Hongsheng Liu, Bin Dong, Meta-Auto-Decoder: A Meta-Learning
Based Reduced Order Model for Solving Parametric Partial Differential Equations,
Communications on Applied Mathematics and Computation,
doi.org/10.1007/s42967-023-00293-7, 2023 (arXiv:2302.08263).
6.
Wei Wan, Yuejin Zhang, Chenglong Bao, Bin Dong, Zuoqiang
Shi, A scalable deep learning
approach for solving high-dimensional dynamic optimal transport, SIAM
Journal on Scientific Computing, 45(4), B544-B563, 2023
(arXiv:2205.07521).
7.
Zhiwen Deng, Jing
Wang, Hongsheng Liu, Hairun
Xie, BoKai Li, Miao Zhang, Tingmeng Jia, Yi Zhang, Zidong Wang,
Bin Dong, Prediction of transonic
flow over supercritical airfoils using geometric-encoding and deep-learning
strategies, Physics of Fluids, DOI: 10.1063/5.0155383, 2023
(arXiv:2303.03695).
8.
Zhengyi Li, Bin Dong and Yanli
Wang, Learning Invariance Preserving
Moment Closure Model for Boltzmann-BGK Equation, Communications in
Mathematics and Statistics, 11(1), 59-101, 2023
(arXiv:2110.03682).
9.
Xiang Huang, Zhanhong Ye, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya
Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei
Hua, Lei Chen, Bin Dong, Meta-Auto-Decoder
for Solving Parametric Partial Differential Equations, NeurIPS
2022, spotlight (arXiv:2111.08823).
10.
Hexin Dong, Zifan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, Li Zhang, Region-Aware
Metric Learning for Open World Semantic Segmentation via Meta-Channel
Aggregation, IJCAI 2022.
11.
Xiang Huang, Hongsheng
Liu, Beiji Shi, Zidong
Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin
Dong, Solving Partial Differential
Equations with Point Source Based on Physics-Informed Neural Networks,
IJCAI 2022 (arXiv:2111.01394).
12.
Stefan
C. Schonsheck, Bin Dong and Rongjie
Lai, Parallel
Transport Convolution: A New Tool for Convolutional Neural Networks on
Manifolds, SIAM Journal on Imaging Science, 15(1), 367-386, 2022 (arXiv:1805.07857).
13.
Yuyan Chen, Bin
Dong, Jinchao Xu, Meta-MgNet: Meta Multigrid Networks for
Solving Parameterized Partial Differential Equations, Journal of
Computational Physics, 455, 110996, 2022 (arXiv:2010.14088).
14.
Jin Zhao, Weifeng Zhao, Zhiting Ma, Wen-An Yong, Bin Dong,
Finding
Models of Heat Conduction via Machine Learning, International Journal of
Heat and Mass Transfer, 185, 122396,
2022.
15. Pengfei Jin, Tianhao
Lai, Rongjie Lai and Bin Dong, NPTC-net: Narrow-Band Parallel
Transport Convolutional Neural Network on Point Clouds, Journal of
Scientific Computing, 90 (39), 2021 (arXiv:
1905.12218).
16. Qi Sun, Hexin Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong,
A Practical Layer-Parallel
Training Algorithm for Residual Networks, NeurIPS
2021 Workshop on Deep Learning and Differential Equations, 2021
(arXiv:2009.01462).
17. Chizhou Liu, Yunzhen Feng, Ranran Wang and Bin Dong, Enhancing Certified
Robustness of Smoothed Classifiers via Weighted Model Ensembling, ICML 2021
Workshop on Adversarial
Machine Learning, (arXiv:2005.09363).
18. Fei Yu, Mo
Zhang, Hexin Dong, Sheng Hu, Bin Dong, Li Zhang, DAST:
Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator
Attention and Self-Training, AAAI 2021.
19. Haiwen Huang, Zhihan Li, Lulu
Wang, Sishuo Chen, Bin Dong, Xinyu
Zhou, Feature Space Singularity for
Out-of-Distribution Detection, AAAI Workshop
on SafeAI, 2021 (arXiv:2011.14654).
20.
Yufei Wang, Ziju Shen, Zichao Long and Bin
Dong, Learning to Discretize:
Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning, Communications
in Computational Physics, 28, 2158-2179, 2020 (arXiv:
1905.11079).
21.
Junyu Liu, Xiao Wang, Yan Zhao, Bin Dong, Kuan Lu and Ranran Wang, Heating
Load Forecasting for Combined Heat and Power Plants via Strand-Based LSTM,
IEEE Access, 8, 33360-33369, 2020.
22. Bin Dong, Jikai Hou, Yiping Lu and Zhihua
Zhang, Distillation ≈ Early Stopping? Harvesting Dark Knowledge
Utilizing Anisotropic Information Retrieval for Overparameterized Neural
Network, NeurIPS 2019 Workshop on Machine
Learning with Guarantees, (arXiv:1910.01255).
23. Yiping Lu, Zhuohan Li, Di He, Zhiqing Sun,
Bin Dong, Tao Qin, Liwei wang, Tie-Yan Liu, Understanding and Improving
Transformer from a Multi-Particle Dynamic System Point of View, NeurIPS 2019, Workshop on Machine Learning
and the Physical Sciences (arXiv: 1906.02762).
24. Dinghuai Zhang, Tianyuan
Zhang, Yiping Lu, Zhanxing Zhu, Bin Dong, You
Only Propagate Once: Accelerating Adversarial Training Using Maximal Principle,
NeurIPS 2019 (arXiv:1905.00877).
25.
Zichao Long, Yiping Lu and Bin Dong, PDE-Net
2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network,
Journal of Computational Physics, 399,
108925, 2019 (arXiv:1812.04426).
26.
Haiwen Huang, Chang Wang and Bin Dong, Nostalgic
Adam: Weighing more of the past gradients when designing the adaptive learning
rate, IJCAI 2019 (arXiv:1805.07557).
27.
Xiaoshuai Zhang, Yiping Lu, Jiaying
Liu and Bin Dong, Dynamically Unfolding
Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration,
ICLR 2019 (arXiv:1805.07709).
28.
Yiping
Lu, Aoxiao Zhong, Quanzheng
Li and Bin Dong, Beyond
Finite Layer Neural Networks: Bridging Deep Architectures and Numerical
Differential Equations, Thirty-fifth International Conference on Machine
Learning (ICML), 2018 (arXiv:1710.10121).
29.
Zichao Long, Yiping Lu, Xianzhong
Ma and Bin Dong, PDE-Net:
Learning PDEs from Data, Thirty-fifth International Conference on Machine
Learning (ICML), 2018 (arXiv:1710.09668).
Codes, Supplementary
Materials
30.
Yue
Selena Niu, Ning Hao and Bin Dong, A new reduced-rank linear discriminant
analysis method and its applications, Statistica
Sinica,28,189-202, 2018.
31.
Bin
Dong, Sparse Representation on
Graphs by Tight Wavelet Frames and Applications, Applied and Computational
Harmonic Analysis, 42(3), 452-479,
2017.
MATLAB Codes: Fast
tight wavelet frame transform on graphs (WFTG);
Graph Clustering
by WFTG.
32.
Bin
Dong and Ning Hao, Semi-supervised
high dimensional clustering by tight wavelet frames, Proceedings of SPIE,
Wavelets & Sparsity XVI, Aug. 2015.
MATLAB Codes (for second row of Table 1)
33.
Ning
Hao, Bin Dong and Jianqing Fan, Sparsifying the Fisher Linear Discriminant by
Rotation, Journal of the Royal Statistical Society Series B, 77(4), 827-851, 2015.
MATLAB
Codes (Rotation)
Machine Learning for Medical Imaging and Data
Analysis
1.
Jiajia Yuan, Peng Bao, Zifan
Chen, Mingze Yuan, Jie
Zhao, Jiahua Pan, Yi Xie, Yanshuo Cao, Yakun Wang, Zhenghang Wang, Zhihao Lu, Xiaotian Zhang, Jian Li, Lei Ma, Yang Chen, Li Zhang, Lin
Shen and Bin Dong, Advanced
Prompting as a Catalyst: Empowering Large Language Models in the Management of
Gastrointestinal Cancers, The Innovation Medicine, 1(2), 100019, 2023.
2.
Hexin Dong, Jiawen Yao, Yuxing Tang, Mingze Yuan, Yingda Xia, Jian Zhou, Hong Lu, Jingren
Zhou, Bin Dong, Le Lu, Li Zhang, Zaiyi Liu, Yu Shi,
Ling Zhang, Improved Prognostic
Prediction of Pancreatic Cancer Using Multi-Phase CT by Intergrating Neural
Distance and Texture-Aware Transformer, MICCAI 2023.
3.
Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng
Li, Unsupervised Image Denoising
with Score Function, NeurIPS 2023
(arXiv:2304.08384).
4.
Mingze Yuan, Yingda Xia, Xin
Chen, Jiawen Yao, Junli
Wang, Mingyan Qiu, Hexin Dong, Jingren Zhou, Bin
Dong, Le Lu, Li Zhang, Zaiyi Liu and Ling Zhang, Cluster-Induced Mask Transformers
for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans,
MICCAI 2023.
5.
Meng
He, Zi-Fan Chen, Li Zhang, Xiangyu Gao, Xiaoyi Chong, Hao-shen Li, Lin
Shen, Jiafu Ji, Xiaotian
Zhang, Bin Dong, Zi-Yu Li and Tang Lei, Associations of subcutaneous
fat area and Systemic Immune-inflammation Index with survival in patients with
advanced gastric cancer receiving dual PD-1 and HER2 blockade, Journal of ImmunoTherapy of Cancer, 11:e007054, 2023.
6.
Chaoyan Huang, Tingting Wu, Juncheng Li, Bin Dong, Tieyong
Zeng, Single-Particle
Reconstruction in Cryo-EM based on Three-dimensional Weighted Nuclear Norm
Minimization, Pattern Recognition, doi.org/10.1016/j.patcog.2023.109736,
2023.
7.
Mingze Yuan, Yingda Xia, Hexin Dong, Zifan Chen, Jiawen Yao, Mingyan Qiu, Ke Yan, Xiaoli
Yin, Yu Shi, Xin Chen, Zaiyi Liu, Bin Dong, Jingren Zhou, Le Lu, Ling Zhang, Li Zhang, Devil is in
the Queries: Advancing Mask Transformers for Real-world Medical Image
Segmentation, OOD Detection and Localization, CVPR 2023.
8.
Jiazheng Li, Zifan Chen, Yang
Chen, Jie Zhao, Meng He, Xiaoting
Li, Li Zhang, Bin Dong, Xiaotian Zhang, Lei Tang, Lin
Shen, CT-based
delta radiomics in predicting the prognosis of stage IV gastric cancer to
immune checkpoint inhibitors, Frontiers in Oncology,
10.3389/fonc.2022.1059874, 2023.
9.
Yang
Chen, Keren Jia, Yu Sun, Cheng Zhang, Yilin Li, Li Zhang, Zifan
Chen, Jiangdong Zhang, Yajie
Hu, Jiajia Yuan, Xingwang
Zhao, Yanyan Li, Jifang
Gong, Bin Dong, Xiaotian Zhang, Jian Li and Lin Shen,
Predicting
response to immunotherapy in gastric cancer via multi-dimensional analyses of
the tumour immune microenvironment, Nature Communications, 13:4851, 2022.
10.
Qilin Zhang, Peng Bao, Ang Qu, Weijuan
Jiang, Ping Jiang, Hongqing Zhuang, Bin Dong, Ruijie Yang, The
feasibility study on the generalization of deep learning dose prediction model
for volumetric modulated arc therapy of cervical cancer, Journal of Applied
Clinical Medical Physics, 23(6),
e13583, 2022.
11.
Chenglong Bao, Jian-Feng Cai, Jae Kyu
Choi, Bin Dong, and Ke Wei, Improved
Harmonic Incompatibility Removal for Susceptibility Mapping via Reduction of
Basis Mismatch, Journal of Computational Mathematics, 40(6), 914-937, 2022.
12.
Mo
Zhang, Bin Dong and Quanzheng Li, Joint
Attention for Medical Image Segmentation, ISBI 2022. (Supplementary)
13.
Mo
Zhang, Bin Dong and Quanzheng Li, MS-GWNN:
Multi-Scale Graph Wavelet Neural Network for Breast Cancer Diagnosis, ISBI
2022. (Supplementary)
14.
Ziju Shen, Yufei Wang, Dufan Wu, Xu Yang and
Bin Dong, Learning to Scan: A Deep
Reinforcement Learning Approach for Personalized Scanning in CT Imaging,
Inverse Problems and Imaging, 16(1), 179, 2022 (arXiv:2006.02420).
15.
Ti Bai, Biling Wang, Dan
Nguyen, Bao Wang, Bin Dong, Wenxiang Cong, Mannudeep K. Kalra and Steve
Jiang, Deep Interactive
Denoiser (DID) for X-Ray Computed Tomography, IEEE Transactions on Medical
Imaging, 40(11), 2965-2975, 2021
(arXiv:2011.14873).
16.
Ce
Wang, Haimiao Zhang, Qian Li, Kun
Shang, Yuanyuan Lyu, Bin Dong, S. Kevin. Zhou, Generalizable Limited-Angle CT
Reconstruction via Sinogram Extrapolation, MICCAI 2021 (arXiv:2103.05255).
17.
Peiting You, Xiang Li, Zhijiang
Wang, Huali Wang, Bin Dong and Quanzheng
Li, Characterization
of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor
in Alzheimer’s
Disease Using Susceptibility-Weighted Imaging, Front. Hum. Neurosci., 15,
654381, 2021.
18.
Bin
Dong, Haochen Ju, Yiping Lu and Zuoqiang Shi, CURE:
Curvature Regularization For Missing Data Recovery, SIAM Journal on Imaging
Science, 13(4), 2169-2188, 2020 (arXiv:1901.09548).
19.
Haimiao Zhang, Baodong Liu, Hengyong Yu and Bin Dong, MetaInv-Net: Meta Inversion
Network for Sparse View CT Image Reconstruction, IEEE Transactions on
Medical Imaging, 40(2), 621–634, 2021 (arXiv:2006.00171).
20.
Mo
Zhang, Bin Dong and Quanzheng Li, Deep
Active Contour Network for Medical Image Segmentation, MICCAI 2020.
21.
Fei Yu, Hexin Dong, Mo
Zhang, Jie Zhao, Bin Dong, Quanzheng
Li, Li Zhang, AF-SEG: an
Annotation-Free Approach for Image Segmentation by Self-Supervision and
Generative Adversarial Network, IEEE International Symposium on Biomedical
Imaging (ISBI20), 2020.
22.
Hexin Dong, Fei
Yu, Jiang Han, Zhang Hua, Bin Dong, Quanzheng Li, Li
Zhang, Annotation-Free
Gliomas Segmentation Based on a Few Labeled General Brain Tumor Images,
IEEE International Symposium on Biomedical Imaging (ISBI20), 2020.
23.
Yini Pan, Hongfeng Li,
Lili Liu, Quanzheng Li, Xinlin
Hou and Bin Dong, aEEG Signal
Analysis with Ensemble Learning for Newborn Seizure Detection, MICCAI
Workshop on MMMI, 2019.
24.
Fei
Yu, Jie Zhao, Yanjun Gong, Zhi Wang, Yuxi Li, Fan Yang, Bin
Dong, Quanzheng Li and Li Zhang, Annotation-Free
Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images,
MICCAI 2019.
25.
Haimiao Zhang, Bin Dong and Baodong
Liu, JSR-Net:
A Deep Network for Joint Spatial-Radon Domain CT Reconstruction from incomplete
data, the International Conference on Acoustics, Speech, and Signal
Processing (IEEE-ICASSP 2019), 2019
(arXiv:1812.00510)
26.
Geng Chen, Bin Dong, Yong Zhang, Weili
Lin, Dinggang Shen and Pew-Thian
Yap, XQ-SR:
Joint x-q Space Super-Resolution with Application to Infant Diffusion MRI,
Medical Image Analysis, doi:
https://doi.org/10.1016/j.media.2019.06.010, 2019.
27.
Geng Chen, Bin Dong, Yong Zhang, Weili
Lin, Dinggang Shen and Pew-Thian
Yap, Denoising of
Diffusion MRI Data via Graph Framelet Matching in x-q Space, IEEE
Transactions on Medical Imaging, DOI: 10.1109/TMI.2019.2915629, 2019.
28.
Chenglong Bao, Jae Kyu Choi and
Bin Dong, Whole
Brain Susceptibility Mapping Using Harmonic Incompatibility Removal, SIAM
Journal on Imaging Science, 12(1), 492-520, 2019 (arXiv1805.12521).
29.
Geng Chen, Jian Zhang, Yong Zhang, Bin Dong, Dinggang Shen and Pew-Thian Yap, Multi-channel
framelet denoising of diffusion weighted images, PLoS
ONE, 14(2): e0211621, 2019.
30.
Geng Chen, Bin Dong, Yong Zhang, Weili
Lin, Dinggang Shen and Pew-Thian
Yap, Angular
upsampling in infant diffusion MRI using neighborhood matching in x-q space,
Front. Neuroinform. 12:57. doi:
10.3389/fninf.2018.00057.
31.
Dufan Wu, Kyungsang Kim,
Bin Dong, Georges El Fakhri and Quanzheng Li, End-to-End
Lung Nodule Detection in Computed Tomography, MICCAI Workshop, 2018
(arXiv:1711.02074).
32.
Zenghui Wei, Baodong Liu, Bin
Dong and Long Wei, A joint
reconstruction and segmentation method for limited-angle X-ray tomography,
IEEE Access, 6(1), 7780-7791, 2018.
33.
Haimiao Zhang, Bin Dong and Baodong
Liu, A
Re-weighted Joint Spatial-Radon Domain CT Image Reconstruction Model for Metal
Artifact Reduction, SIAM Journal on Imaging Science, 11(1), 707-733, 2018.
34.
Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian
Yap, q-Space
Upsampling Using x-q Space Regularization, MICCAI 2017, 620-628.
35.
Geng Chen, Bin Dong, Yong Zhang, Dinggang Shen, Pew-Thian
Yap, Neighborhood
Matching for Curved Domains with Application to Denoising in Diffusion MRI,
MICCAI 2017, 629-637.
36.
Pew-Thian Yap, Bin Dong, Yong Zhang and Dinggang
Shen, Tight
Graph Framelets for Sparse Diffusion MRI q-Space Representation,
MICCAI 2016, 561-569.
37.
Yu
Yang, Bin Dong and Zaiwen Wen, Randomized
Algorithms For High Quality Treatment Planning in Volumetric Modulated Arc
Therapy, Inverse Problems, 32(2),025007,2017.
38.
Jae
Kyu Choi, Bin Dong and Xiaoqun
Zhang, Limited
Tomography Reconstruction via Tight Frame and Simultaneous Sinogram
Extrapolation, Journal of Computational Mathematics, 34(6), 575-589,2016.
39.
Ruohan Zhan and Bin Dong, CT Image
Reconstruction by Spatial-Radon Domain Data-Driven Tight Frame Regularization,
SIAM Journal on Imaging Sciences, 9(3), 1063-1083,2016.
Matlab Codes: SRD-DDTF (This package includes codes for our earlier
work: Dong, Li and Shen, X-ray CT image
reconstruction via wavelet frame based regularization and Radon domain
inpainting, JSC, 2013)
40. Jiulong Liu, Xiaoqun Zhang, Bin Dong, Zuowei Shen and Lixu Gu, A wavelet frame method with shape prior for ultrasound video segmentation, SIAM Journal on Imaging Sciences, 9(2), 495-536. 2016. (This article is spotlighted by SIAM in "SIAM Nuggets", and was also reported in various websites: SIAM.NEWS; Science_News; ScienceDaily; Scifeeds; Science_Codex; EurekAlert; MedImaging; Hitechdays; TechXplore; Technobahn; Pubniche; Healthmanagement.org; Healthcarebusiness; AuntMinnie; Myinforms; OOYUZ; Wrightwood)
41. Li-Tien Cheng, Bin Dong, Chunhua Men, Xun Jia and Steve B. Jiang, Binary Level-Set Shape Optimization Model and Algorithm for Volumetric Modulated Arc Therapy in Cancer Radiotherapy, SIAM Journal on Scientific Computing, 35(6), 1321-1340, 2013.
42. Xuejun Gu, Bin Dong, Jing Wang, John Yordy, Loren Mell, Xun Jia, and Steve B. Jiang, A Contour-Guided Deformable Image Registration Algorithm for Adaptive Radiotherapy, Physics in Medicine and Biology, 58(6). 1889, 2013.
43. Bin Dong, Jia Li and Zuowei Shen, X-ray CT image reconstruction via wavelet frame based regularization and Radon domain inpainting, Journal of Scientific Computing, 54(2-3), 333-349 2013.
44. Bin Dong, Yan Jiang Graves, Xun Jia and Steve B. Jiang, Optimal Surface Marker Locations for Tumor Motion Estimation in Lung Cancer Radiotherapy, Physics in Medicine and Biology, 57(24), 8201, 2012
45. Bin Dong and Zuowei Shen, MRA-based wavelet frames and applications: image segmentation and surface reconstruction, Processing of SPIE, Defense, Security and Sensing, Vol 8401, 2012.
46. Xun Jia, Bin Dong, Yifei Lou and Steve B. Jiang, GPU-based iterative cone beam CT reconstruction using tight frame regularization, Physics in Medicine and Biology, 56, 3787-3807 2011.
47. Aichi Chien, James Sayre, Bin Dong, Jian Ye and Fernando Vinuela, 3D Quantitative Evaluation of Atherosclerotic Plaque based on Rotational Angiography, American Journal of Neuroradiology, 32, 1249-1254, 2011.
48. Zhen Tian, Xun Jia, Bin Dong, Yifei Lou and Steve B. Jiang, Low-dose 4DCT reconstruction via temporal nonlocal means, Medical Physics, 38(3), March 2011.
49. Bin Dong, Aichi Chien and Zuowei Shen, Frame based segmentation for medical images, Communications in Mathematical Sciences, 9(2), 551-559, 2011.
50. Daren Lee, Ivo Dinov, Bin Dong, Boris Gutman, Igor Yanovsky and Arthur W. Toga, CUDA Optimization strategies for compute- and memory-bound neuroimaging algorithms, Computer Methods and Programs in Biomedicine, Elsevier, 2010.
51. Bin Dong, Aichi Chien, Zuowei Shen and Stanley Osher, A new multiscale representation for shapes and its application to blood vessel recovery, SIAM Journal on Scientific Computing, 32(4), 1724-1739, 2010.
52. Xun Jia, Yifei Lou, Bin Dong, Zhen Tian and Steve Jiang, 4D computed tomography reconstruction from few-projection data via temporal non-local regularization, MICCAI 2010, Beijing, China, Sep 20-24, 2010.
53. Bin Dong, Aichi Chien, Yu Mao, Jian Ye, Fernando Vinuela and Stanley Osher, Level set based brain aneurysm capturing in 3D, Inverse Problems and Imaging (special issue in medical image analysis), 4(2), 241-255, 2010.
54. Bin Dong, Eric Savitsky and Stanley Osher, A novel method for enhanced needle localization using ultrasound-guidance, Advances in Visual Computing: Part I, 914-923, 2009 (5th International Symposium on Visual Computing, ISVC 2009, Las Vegas, Nevada, USA).
55. Bin Dong, Yu Mao, Ivo D. Dinov, Zhuowen Tu, Yonggang Shi, Yalin Wang and Arthur W. Toga, Wavelet-based representation of biological shapes, Advances in Visual Computing: Part I, 955-964, ISVC 2009 (5th International Symposium on Visual Computing, ISVC 2009, Las Vegas, Nevada, USA).
56.
Bin
Dong, Aichi Chien, Yu Mao, Jian Ye and Stanley Osher, Level set
based surface capturing in 3D medical images, MICCAI 2008, 162-169, 2008.
Mathematical Image Processing and Analysis
1.
Bin
Dong, Zuowei Shen and Jianbin
Yang, Approximation
from Noisy Data, SIAM Journal on Numerical Analysis, 59(5), 2722-2745, 2021.
2.
Jae
Kyu Choi, Bin Dong and Xiaoqun
Zhang, An
Edge Driven Wavelet Frame Model for Image Restoration, Applied and
Computational Harmonic Analysis, 48(3):993-1029, 2020.
MATLAB Codes (for deblurring and inpainting)
3. Bin Dong, Qingtang Jiang and Zuowei Shen, Image restoration: wavelet frame shrinkage, nonlinear evolution PDEs, and beyond, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 15(1),606-660, 2017.
MATLAB Codes (for Table 2 and Table 3 with image example "Peppers")
4. Bin Dong, Zuowei Shen and Peichu Xie, Image restoration: a general wavelet frame based model and its asymptotic analysis, SIAM Journal on Mathematical Analysis, 49(1), 421-445, 2017.
5. Jian-Feng Cai, Bin Dong and Zuowei Shen, Image restoration: a wavelet frame based model for piecewise smooth functions and beyond, Applied and Computational Harmonic Analysis, 41(1), 94-138, 2016.
6. Chenglong Bao, Bin Dong, Likun Hou, Zuowei Shen and Xiaoqun Zhang, Xue Zhang, Image restoration by minimizing zero norm of wavelet frame coefficients, Inverse Problems, 32(11), 2016.
7. Bin Dong, Qingtang Jiang, Chaoqiang Liu and Zuowei Shen, Multiscale Representation of Surfaces by Tight Wavelet Frames with Applications to Denoising, Applied and Computational and Harmonic Analysis, 41(2), 561-589, 2016.
8. Bin Dong and Yong Zhang, An efficient algorithm for l0 minimization in wavelet frame based image restoration, Journal of Scientific Computing, 54(2-3), 350-368, 2013.
9. Yong Zhang, Bin Dong and Zhaosong Lu, l0 minimization of wavelet frame based image restoration, Mathematics of Computation, 82, 995-1015, 2013.
10. Jian-Feng Cai, Bin Dong, Stanley Osher and Zuowei Shen, Image restoration: total variation; wavelet frames; and beyond, Journal of the American Mathematical Society, 25(4), 1033-1089, 2012.
11. Jian Ye, Igor Yanovsky, Bin Dong, Rima Gandlin, Achi Brandt and Stanley Osher, Multigrid narrow band surface reconstruction via level set functions, 8th International Symposium on Visual Computing (ISVC), July 16-18, 2012, Greece.
12. Bin Dong, Hui Ji, Jia Li, Zuowei Shen and Yuhong Xu, Wavelet frame based blind image inpainting, Applied and Computational Harmonic Analysis, 32(2), 268-279, 2012.
13. Bin Dong and Zuowei Shen, Wavelet frame based surface reconstruction from unorganized points, Journal of Computational Physics, 230(22), 8247-8255, 2011.
14. Yu Mao, Bin Dong and Stanley Osher, A nonlinear PDE-based method for sparse deconvolution, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 8(3), 965-976, 2010.
15. Stanley Osher, Yu Mao, Bin Dong and Wotao Yin, Fast linearized Bregman iterations for compressive sensing and sparse denoising, Communications in Mathematical Sciences, 8(1), 93-111, 2010.
16. Bin Dong, Nira Dyn and Kai Hormann, Properties of dual pseudo-splines, Applied and Computational Harmonic Analysis, 29(1), 104-110, 2010.
17. Bin Dong, Jian Ye, Stanley Osher and Ivo Dinov, Level set based nonlocal surface restoration, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, Vol. 7(2), 589-598, 2008.
18. Bin Dong and Zuowei Shen, Pseudo-splines, wavelets and framelets, Applied and Computational Harmonic Analysis, 22, 78-104, 2007.
19. Bin Dong and Zuowei Shen, Linear independence of pseudo-splines, Proceedings of American Mathematical Society, 134, 2685-2694, 2006.
20. Bin Dong and Zuowei Shen, Construction of biorthogonal wavelets from pseudo-splines, Journal of Approximation Theory, Vol. 138 (2), 211-231, 2006.
Book (Chapters) /Review Papers
1.
Bin
Dong, On
Mathematical Modeling in Image Reconstruction and Beyond, Proceedings of
the International Congress of Mathematicians, International Mathematical Union
(Virtual Meeting),
2022.
2.
Chenyang Shen, Dan Nguyen, Zhiguo
Zhou, Steve B. Jiang, Bin Dong, and Xun Jia, An introduction
to deep learning in medical physics: advantages, potential, and challenges,
Physics in Medicine and Biology, 65(5): 05TR01-, 2020.
3.
董彬,图像反问题中的数学与深度学习方法,计算数学,第41卷、第4期,2019年11月
4.
Haimiao Zhang and
Bin Dong, A
Review on Deep Learning in Medical Image Reconstruction, Journal of the
Operations Research Society of China, 8(2):311-340, 2020 (arXiv: 1906.10643).
5.
欧高炎、朱占星、董彬、鄂维南,数据科学导引,高等教育出版社,2017年12月
6.
董彬、沈佐伟、张小群,图象恢复问题中的数学方法,中科院数学所讲座系列(席南华
主编),科学出版社,2017.
7. Bin Dong and Zuowei Shen, Image restoration: a data-driven perspective, Proceedings of the International Congress of Industrial and Applied Mathematics (ICIAM), Beijing, China, High Education Press (Lei Guo and Zhi-Ming Ma eds), 65-108, 2015.
8. Bin Dong and Zuowei Shen, MRA-based wavelet frames and applications, IAS Lecture Notes Series, Hong-Kai, ed. "Mathematics in Image Processing". Vol. 19. American Mathematical Society, 2013.
Technical Reports
1. Yifan Luo and Bin Dong, Double Descent of Discrepancy: A Task-,
Data-, and Model-Agnostic Phenomenon, arXiv:2305.15907.
2. Yutong Xie, Mingze Yuan, Bin Dong, Quanzheng Li, Diffusion
Model for Generative Image Denoising, arXiv:2302.02398.
3. Hexin Dong, Fei Yu, Mingze
Yuan, Jie Zhao, Bin Dong and Li Zhang, Unsupervised
Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and
Self-Training (PAST), 2022. (This is the technical report of the 1st place of CrossMoDA challenge 2022 -
segmentation task.)
4. Bin Dong, A Note on Machine Learning Approach for
Computational Imaging, arXiv:2202.11883, 2022.
5. Yutong Xie, Dufan Wu, Bin Dong, Quanzheng Li, Trained
Model in Supervised Deep Learning is a Conditional Risk Minimizer,
arXiv:2202.03674.
6. Qi Sun, Hexin Dong, Zewei Chen, Jiacheng Sun, Zhenguo Li, Bin
Dong, Layer-Parallel Training of
Residual Networks with Auxiliary-Variable Networks, arXiv:2112.05387.
7. Hexin Dong, Fei Yu, Jie Zhao,
Bin Dong and Li Zhang, Unsupervised
Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and
Self-Training, arXiv:2109.14219. (This is
the technical report of the 2nd place of
CrossMoDA challenge 2021.)
8. Yunzhen Feng, Runtian Zhai, Di He, Liwei Wang, Bin
Dong, Transferred Discrepancy:
Quantifying the Difference Between Representations, arXiv:2007.12446, 2020.
9. Junyu Liu, Zichao Long, Ranran Wang, Jie Sun and Bin
Dong, RODE-Net: Learning Ordinary
Differential Equations with Randomness from Data, arXiv:2006.02377, 2020.
10.
Robert
Crandall, Bin Dong and Ali Bilgin, Randomized Iterative Hard Thresholding: A Fast
Approximate MMSE Estimator for Sparse Approximations, Technical Report,
June 2013 (revised, April 2014).
Others
1.
“AI for
Mathematics:数学智能副驾驶的构想”,北京国际数学研究中心公众号,2023年6月16日。
2.
“用深度神经网络学习偏微分方程及其数值求解的离散格式”,北京智源人工智能研究院,2020年1月19日。
3.
“天生一对,硬核微分方程与深度学习的「联姻」之路”,机器之心,2019年5月17日。
4.
Bin
Dong, The implicit representation
of biological shapes and forms, Biomedical
Computation Review (issue: Spring 2009), Published by Simbios, the NIH National Center for Physics-Based
Simulation of Biological Structures, 2009.
5.
Bin
Dong, Applications of Variational Models and
Partial Differential Equations in Medical Image and Surface Processing, PhD
Thesis, UCLA, 2009.
6.
Bin Dong, Pseudo-splines, Wavelets and
Framelets, M.S. Thesis, National University of Singapore, 2005.