Xiaojing Ye

Orcid: 0000-0002-0516-4974

According to our database1, Xiaojing Ye authored at least 60 papers between 2008 and 2024.

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Bibliography

2024
Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction.
J. Sci. Comput., October, 2024

Infrared Image Super-Resolution Network Utilizing the Enhanced Transformer and U-Net.
Sensors, July, 2024

An End-to-End Mutually Exclusive Autoencoder Method for Analog Circuit Fault Diagnosis.
J. Electron. Test., February, 2024

Neural Control of Parametric Solutions for High-Dimensional Evolution PDEs.
SIAM J. Sci. Comput., 2024

Parameterized Wasserstein Gradient Flow.
CoRR, 2024

Approximation of Solution Operators for High-dimensional PDEs.
CoRR, 2024

2023
Approximating High-Dimensional Minimal Surfaces with Physics-Informed Neural Networks.
CoRR, 2023

Parameterized Wasserstein Hamiltonian Flow.
CoRR, 2023

Low-rank matrix recovery with unknown correspondence.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Learned Alternating Minimization Algorithm for Dual-Domain Sparse-View CT Reconstruction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

High-Dimensional Optimal Density Control with Wasserstein Metric Matching.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022
Extra Proximal-Gradient Network with Learned Regularization for Image Compressive Sensing Reconstruction.
J. Imaging, 2022

A Learnable Variational Model for Joint Multimodal MRI Reconstruction and Synthesis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Lyapunov-Net: A Deep Neural Network Architecture for Lyapunov Function Approximation.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Learnable Descent Algorithm for Nonsmooth Nonconvex Image Reconstruction.
SIAM J. Imaging Sci., 2021

An Optimization-Based Meta-Learning Model for MRI Reconstruction with Diverse Dataset.
J. Imaging, 2021

An Optimal Control Framework for Joint-channel Parallel MRI Reconstruction without Coil Sensitivities.
CoRR, 2021

Influence Estimation and Maximization via Neural Mean-Field Dynamics.
CoRR, 2021

A Hypergradient Approach to Robust Regression without Correspondence.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Weak adversarial networks for high-dimensional partial differential equations.
J. Comput. Phys., 2020

A Novel Learnable Gradient Descent Type Algorithm for Non-convex Non-smooth Inverse Problems.
CoRR, 2020

Numerical Solution of Inverse Problems by Weak Adversarial Networks.
CoRR, 2020

Learning Cost Functions for Optimal Transport.
CoRR, 2020

Acceleration techniques for level bundle methods in weakly smooth convex constrained optimization.
Comput. Optim. Appl., 2020

Network Diffusions via Neural Mean-Field Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Deep Parallel MRI Reconstruction Network Without Coil Sensitivities.
Proceedings of the Machine Learning for Medical Image Reconstruction, 2020

2019
A Two-Stage Algorithm for Joint Multimodal Image Reconstruction.
SIAM J. Imaging Sci., 2019

Learning to Match via Inverse Optimal Transport.
J. Mach. Learn. Res., 2019

2018
Decentralized Consensus Algorithm with Delayed and Stochastic Gradients.
SIAM J. Optim., 2018

Asynchronous broadcast-based decentralized learning in sensor networks.
Int. J. Parallel Emergent Distributed Syst., 2018

Influence prediction for continuous-time information propagation on networks.
Networks Heterog. Media, 2018

Learning to Recommend via Inverse Optimal Matching.
CoRR, 2018

Learning Deep Mean Field Games for Modeling Large Population Behavior.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Deep Mean Field Games for Learning Optimal Behavior Policy of Large Populations.
CoRR, 2017

Wasserstein Learning of Deep Generative Point Process Models.
CoRR, 2017

Wasserstein Learning of Deep Generative Point Process Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Predicting User Activity Level In Point Processes With Mass Transport Equation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Fake News Mitigation via Point Process Based Intervention.
Proceedings of the 34th International Conference on Machine Learning, 2017

Linking Micro Event History to Macro Prediction in Point Process Models.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Multistage Campaigning in Social Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Consensus optimization with delayed and stochastic gradients on decentralized networks.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Potential induced random teleportation on finite graphs.
Comput. Optim. Appl., 2015

Fast decentralized gradient descent method and applications to in-situ seismic tomography.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Coarse-to-Fine Classification via Parametric and Nonparametric Models for Computer-Aided Diagnosis.
CoRR, 2014

2013
An Efficient Algorithm for Multiphase Image Segmentation With Intensity Bias Correction.
IEEE Trans. Image Process., 2013

Bregman operator splitting with variable stepsize for total variation image reconstruction.
Comput. Optim. Appl., 2013

An enhanced approach for simultaneous image reconstruction and sensitivity map estimation in partially parallel imaging.
Proceedings of the IEEE International Conference on Image Processing, 2013

2012
Fast Algorithms for Image Reconstruction with Application to Partially Parallel MR Imaging.
SIAM J. Imaging Sci., 2012

Jensen divergence based SPD matrix means and applications.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

A variational multiphase model for simultaneous MR image segmentation and bias correction.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

Partially parallel MR image reconstruction using sensitivity encoding.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

2011
Fast MR Image Reconstruction for Partially Parallel Imaging With Arbitrary k -Space Trajectories.
IEEE Trans. Medical Imaging, 2011

Computational Acceleration for MR Image Reconstruction in Partially Parallel Imaging.
IEEE Trans. Medical Imaging, 2011

Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2011, 2011

Efficient minimization for dictionary based sparse representation and signal recovery.
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, 2011

Find the intrinsic space for multiclass classification.
Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, 2011

Coarse-to-fine classification via parametric and nonparametric models for computer-aided diagnosis.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2009
A New Algorithm for Inverse Consistent Image Registration.
Proceedings of the Advances in Visual Computing, 5th International Symposium, 2009

MR Image Reconstruction via Sparse Representation: Modeling and Algorithm.
Proceedings of the 2009 International Conference on Image Processing, 2009

2008
Improvement of accuracy in deformable registration in radiation therapy.
Proceedings of the International Conference on Image Processing, 2008


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