Research Interests
Numerical methods and scientific machine learning, such as solving high-dimensional PDEs
Control and data-driven methods for large-scale or high-dimensional computational problems
Analysis and computational methods for stochastic point processes on large heterogeneous networks
Optimization methods for inverse problems, image processing and medical imaging
Acknowledgement
Current research is partially supported by National Science Foundation under grants DMS-2152960, DMS-2307466, and DMS-2409868.
Preprints
List of publications is available on Google Scholar.
Parameterized Wasserstein Gradient Flows
Y. Jin, S. Liu, H. Wu, X. Ye, H. Zhou
[arxiv]
Learning Cost Functions for Optimal Transport
S. Ma, H. Sun, X. Ye, H. Zha, H. Zhou
[arxiv]
Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction
C. Ding, Q. Zhang, G. Wang, X. Ye, Y. Chen
[arxiv]
Published and Accepted
Parameterized Wasserstein Hamiltonian Flows
H. Wu, S. Liu, X. Ye, H. Zhou
SIAM Journal on Numerical Analysis, accepted, 2024.
[arxiv]
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs
N. Gaby, X. Ye, H. Zhou
SIAM Journal on Scientific Computing, 46(3), C155-C185, 2024.
[link][arxiv]
On Optimal Control at the Onset of a New Viral Outbreak
A. Smirnova, X. Ye
Infectious Disease Modelling, 9(4), 995-1006, 2024.
[link]
Optimal Epidemic Control with Nonmedical and Medical Interventions
A. Smirnova, M. Baroonian, X. Ye
Mathematics Special Issue on Mathematical Methods and Models in Epidemiology, 12(18), 2024.
[link]
Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction
Q. Zhang, M. Alvandipour, W. Xia, Y. Zhang, X. Ye, Y. Chen
Journal of Scientific Computing, accepted, 2024.
[arxiv]
High-dimensional Optimal Density Control with Wasserstein Metric Matching
S. Ma, M. Hou, X. Ye, H. Zhou
IEEE Conference on Decisions and Control (CDC), 2023.
[link]
[arxiv]
Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction
C. Ding, Q. Zhang, X. Ye, Y. Chen
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2023.
[link]
[arxiv]
Low-rank Matrix Recovery With Unknown Correspondence
Z. Tang, T.-H. Chang, X. Ye, H. Zha
Uncertainty in Artificial Intelligence (UAI), 2023.
[link]
[arxiv]
Lyapunov-net: A deep neural network architecture for Lyapunov function approximation
N. Gaby, F. Zhang, X. Ye
IEEE Conference on Decision and Control (CDC), 2022.
[link]
[arxiv]
A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis
W. Bian, Y. Chen, X. Ye
International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022.
[link]
[arxiv]
Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction
Q. Zhang, X. Ye, Y. Chen
Journal of Imaging, 8 (7), 178, 2022.
[pdf]
[link]
An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities
W. Bian, Y. Chen, X. Ye
Magnetic Resonance Imaging, 89, 1-11, 2022.
[link]
[arxiv]
Learnable descent algorithm for nonsmooth nonconvex image reconstruction
Y. Chen, H. Liu, X. Ye, Q. Zhang
SIAM Journal on Imaging Sciences, 14(4), 1532-1564, 2021.
[link]
[arxiv]
An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset
W. Bian, Y. Chen, X. Ye, Q. Zhang
Journal of Imaging, 7(11), 231, 2021.
[link]
[arxiv]
Nonsmooth nonconvex LDCT image reconstruction via learned descent algorithm
Q. Zhang, X. Ye, Y. Chen
Developments in X-Ray Tomography XIII, 11840, 2021.
[pdf]
[link]
(Book chapter) Variational Model-Based Deep Neural Networks for Image Reconstruction
Y. Chen, X. Ye, Q. Zhang
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision, Springer International Publishing, 2021.
[pdf]
[link]
A Hypergradient Approach to Robust Regression without Correspondence
Y. Xie, Y. Mao, S. Zuo, H. Xu, X. Ye, T. Zhao, H. Zha
International Conference on Learning Representation (ICLR), 2021.
[link]
[arxiv]
Network Diffusions via Neural Mean-Field Dynamics
S. He, H. Zha, X. Ye
Advances in Neural Information Processing Systems (NeurIPS), 2020.
[link]
[arxiv]
[code]
Numerical Solution of Inverse Problems by Weak Adversarial Networks
G. Bao, X. Ye, Y. Zang, H. Zhou
Inverse Problems, 36(11), 115003, 2020.
[link]
[arxiv]
[Book chapter] Variational Model with Optimization Algorithm
Y. Chen, X. Ye, Q. Zhang
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, Springer, 2020.
[pdf]
[link]
Deep Parallel MRI Reconstruction Network Without Coil Sensitivities
W. Bian, Y. Chen, X. Ye
MICCAI Workshop Machine Learning for Medical Image Reconstruction, 2020.
[link]
[arxiv]
A Jump Stochastic Differential Equation Approach for Influence Prediction on Information Propagation Networks
Y. Zang, G. Bao, X. Ye, H. Zha, H. Zhou
Communications in Mathematical Sciences, 18(8), pp. 2341-2359, 2020.
[link]
[arxiv]
Acceleration Techniques for Level Bundle Methods in Weakly Smooth Convex Constrained Optimization
Y. Chen, X. Ye, W. Zhang
Computational Optimization and Applications, 77, pp. 411–432, 2020.
[link]
[arxiv]
Weak Adversarial Networks for High-dimensional Partial Differential Equations
Y. Zang, G. Bao, X. Ye, H. Zhou
Journal of Computational Physics, 411(15), 109409, 2020.
[link]
[arxiv]
[code]
[Book] Machine Learning for Tomographic Imaging
G. Wang, Y. Zhang, X. Ye, X. Mou
Institute of Physics (IOP) Publishing, 2019.
[link]
A Two-stage Algorithm for Joint Multimodal Image Reconstruction
Y. Chen, B. Li, X. Ye
SIAM Journal on Imaging Sciences, 12(3). pp. 1425-1463, 2019.
[pdf]
[link]
[code]
A Randomized Incremental Primal Dual Method for Decentralized Consensus Optimization
C. Chen, Y. Chen, X. Ye
Analysis and Applications, pp. 1-25, 2019.
[pdf]
[link]
Learning to Recommend via Inverse Optimal Matching
R. Li, X. Ye, H. Zhou, H. Zha
Journal of Machine Learning Research, 20, pp. 1-37, 2019.
[link]
[arxiv]
Influence Prediction for Continuous-Time Information Propagation on Networks
S.-N. Chow, X. Ye, H. Zha, H. Zhou
Networks and Heterogenous Media, 13(4), pp. 567–583, 2018.
[link]
[arxiv]
Learning Deep Mean Field Games for Modeling Large Population Behavior
J. Yang, X. Ye, R. Trivedi, H. Xu, H. Zha (Oral presentation, 2% rate)
International Conference on Learning Representation (ICLR), 2018.
[link]
[arxiv]
Decentralized Consensus Algorithm with Delayed and Stochastic Gradients
B. Sirb, X. Ye
SIAM Journal on Optimization, 28(2), pp. 1232-1254, 2018.
[link]
[arxiv]
Wasserstein Learning of Deep Generative Point Process Models
S. Xiao, M. Farajtabar, X. Ye, J. Yan, L. Song, H. Zha
Advances in Neural Information Processing Systems (NIPS), 30, pp. 3247-3257, 2017.
[link]
[arxiv]
Predicting User Activity Level In Point Process Models With Mass Transport Equation
Y. Wang, X. Ye, H. Zha, L. Song
Advances in Neural Information Processing Systems (NIPS), 30, pp. 1645-1655, 2017.
[pdf]
[link]
Fake News Mitigation via Point Process Based Intervention
M. Farajtabar, J. Yang, X. Ye, H. Xu, R. Trivedi, E. Khalil, S. Li, L. Song, H. Zha
International Conference on Machine Learning (ICML), PMLR, 70, pp. 1097-1106, 2017.
[link]
[arxiv]
Linking Micro Event History to Macro Prediction in Point Process Models
Y. Wang, X. Ye, H. Zhou, H. Zha, L. Song
Artificial Intelligence & Statistics (AISTATS), PMLR, 54, pp. 1375-1384, 2017.
[pdf]
[link]
Asynchronous Broadcast-based Decentralized Learning in Sensor Networks
L. Zhao, W.-Z. Song, X. Ye, Y. Gu
International Journal of Parallel, Emergent and Distributed Systems, pp. 1-19, 2017.
[pdf]
[link]
Consensus Optimization with Delayed and Stochastic Gradients on Decentralized Networks
B. Sirb, X. Ye
IEEE International Conference on Big Data, pp. 76-85, 2016.
[pdf]
[link]
Multistage Campaigning in Social Networks
M. Farajtabar, X. Ye, S. Harati, L. Song, H. Zha
Advances in Neural Information Processing Systems (NIPS), 29, pp. 4718-4726, 2016.
[link]
[arxiv]
Potential Induced Random Teleportation on Finite Graphs
S.-N. Chow, X. Ye, H. Zhou
Computational Optimization and Applications, 61(3), pp. 689-711, 2015.
[pdf]
[link]
Decentralized Seismic Tomography Computing In Cyber-Physical Sensor Systems
L. Zhao, W.-Z. Song, L. Shi, X. Ye
Cyber-Physical Systems, Taylor & Francis, 1(1), pp. 1-22, 2015.
[pdf]
[link]
Fast Decentralized Gradient Descent Method and Applications to In-situ Seismic Tomography
L. Zhao, W.-Z. Song, X. Ye
IEEE International Conference on Big Data, pp. 908-917, 2015.
[pdf]
[link]
Distributed Consensus Optimization for Nonsmooth Image Reconstruction
X. Ye
Journal of the Operations Research Society of China, 3(2), pp. 117-138, 2015.
[pdf]
[link]
Accelerated Barrier Optimization Compressed Sensing for CT Reconstruction with Improved Convergence
T. Niu, X. Ye, Q. Fruhauf, M. Petrongolo, L. Zhu
Physics in Medicine and Biology, 59, pp. 1801-1814, 2014.
[pdf]
[link]
An Enhanced Approach for Simultaneous Image Reconstruction and Sensitivity Map Estimation in Partially Parallel Imaging
M. Liu, Y. Chen, Y. Ouyang, X. Ye, F. Huang
IEEE Proceedings of International Conference of Image Processing, pp. 2314-2318, 2013.
[pdf]
[link]
Fast Total Variation Wavelet Inpainting via Approximated Primal Dual Hybrid Gradient Algorithm
X. Ye, H. Zhou
Inverse Problems and Imaging, 7(3), pp. 1031-1050, 2013.
[pdf]
[link]
[code]
An Efficient Algorithm for Multiphase Image Segmentation with Intensity Bias Correction
H. Zhang, X. Ye, Y. Chen
IEEE Transactions on Image Processing, 22(10), pp. 3842-3851, 2013.
[pdf]
[link]
[code]
Bregman Operator Splitting With Variable Stepsize for Total Variation Image Reconstruction
Y. Chen, W. W. Hager, M. Yashtini, X. Ye, H. Zhang
Computational Optimization and Applications, 54(2), pp. 317-342, 2013.
[pdf]
[link]
[code]
A Variational Multiphase Model for Simultaneous MR Image Segmentation and Bias Correction
H. Zhang, Y. Chen, X. Ye
IEEE Proceedings of International Conference of Image Processing, pp. 3077-3180, 2012.
[pdf]
[link]
[code]
Jensen Divergence Based SPD Matrix Means and Applications
F. Nielsen, M. Liu, X. Ye, B. Vemuri
Proceedings of International Conference on Pattern Recognition, pp. 2841-2844, 2012.
[pdf]
Partially Parallel MR Image Reconstruction Using Sensitivity Encoding
M. Yashtini, W.W. Hager, Y. Chen, X. Ye
IEEE Proceedings of International Conference of Image Processing, pp. 2077-2080, 2012.
[pdf]
[link]
Fast Algorithms for Image Reconstruction Application to Partially Parallel MR Imaging
Y. Chen, W.W. Hager, F. Huang, D. Phan, X. Ye, W. Yin
SIAM Journal on Imaging Sciences, 5(1), pp. 90-118, 2012.
[pdf]
[link]
Modeling and Computations in Image Registration
Y. Chen, X. Ye
Mathematical Modeling and Its Applications, in Chinese, 1(1), pp. 26-37, 2012.
Coarse-to-fine Classification using Parametric and Nonparametric Models for Computer-Aided Diagnosis
M. Liu, L. Lu, X. Ye, S. Yu
ACM Information and Knowledge Management (CIKM), pp. 2509-2512, 2011.
[pdf]
[Book chapter] Inverse Consistent Deformable Image Registration
Y. Chen, X. Ye
Development of Mathematics - The Legacy of Alladi Ramakrishnan in the Mathematical Sciences
K. Alladi, J. Klauder and C.R. Rao (Eds.), pp. 419-440, Springer-Verlag, 2010.
[pdf]
[link]
[code]
Efficient Minimization for Dictionary Based Sparse Representation and Signal Recovery
X. Ye, K. Liu, M. Liu
ACM Proc. of Intl. Sym. on App. Sci. Biomed. & Comm. Tech., 105, pp. 1-5, 2011.
[pdf]
[link]
Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging
X. Ye, Y. Chen, F. Huang
IEEE Transactions on Medical Imaging, 30(5), pp. 1055-1063, 2011.
[pdf]
[link]
[code]
Find the Intrinsic Space for Multiclass Classification
M. Liu, K. Liu, X. Ye
ACM Proc. of Intl. Sym. on App. Sci. Biomed. & Comm. Tech., 105, pp. 1-5, 2011.
[pdf]
[link]
Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries
M. Liu, L. Lu, X. Ye, S. Yu, M. Salganicoff
Proc. Intl. Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 3, pp. 41-48, 2011.
[pdf]
[link]
Fast MR Image Reconstruction for Partially Parallel Imaging Arbitrary k-Space Trajectories
X. Ye, Y. Chen, W. Lin, F. Huang
IEEE Transactions on Medical Imaging, 30(3), pp. 575-585, 2011.
[pdf]
[link]
A Novel Method and Fast Algorithm for MR Image Reconstruction Significantly Under-Sampled Data
Y. Chen, X. Ye, F. Huang
Inverse Problems and Imaging, 4(2), pp. 223-240, 2010.
[pdf]
[link]
A Rapid and Robust Method for Sensitivity Encoding Sparsity Constraints: Self-feeding Sparse SENSE
F. Huang, Y. Chen, W. Yin, W. Lin, X. Ye, W. Guo, A. Reykowski
Magnetic Resonance in Medicine, 64(4), pp. 1078-1088, 2010.
[pdf]
[link]
A New Algorithm for Inverse Consistent Image Registration
X. Ye and Y. Chen
Proceedings of International Symposium on Visual Computing, LNCS, pp. 855-864, 2009.
[pdf]
[link]
[code]
MR Image Reconstruction via Sparse Representation: Modeling and Algorithm
X. Ye, Y. Chen, F. Huang
Proc. Intl. Conf. Image Processing, Computer Vision, and Pattern Recognition, pp. 10-16, 2009.
[pdf]
[link]
Improvement of Accuracy in Deformable Image Registration in Radiation Therapy
X. Ye, Y. Chen
IEEE Proceedings of International Conference of Image Processing, pp. 2420-2423, 2008.
[pdf]
[link]
Dissertation and Thesis
An \(L^\infty\) bound for the Neumann Problem of the Poisson Equations
B.S. Thesis, Peking University, China, Jul. 2005.
[pdf]
|