Computational Imaging GroupUniversity of Wisconsin–Madison

Publications

For a complete list, see Google Scholar.

Showing 175 of 175

Preprints

Published

2026

  • Measurement Score-Based Diffusion Model

    C. Y. Park, S. Shoushtari, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), Rio, Brazil, 2026

  • EigenScore: OOD Detection using Covariance in Diffusion Models

    S. Shoushtari, Y. Wang, X. Shi, M. S. Asif, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), Rio, Brazil, 2026

  • Stochastic Generative Plug-and-Play Priors

    C. Y. Park, E. P. Chandler, Y. Hu,

    IEEE Trans. Comput. Imag., 2026

  • ADOBI: Adaptive Diffusion Bridge For Blind Inverse Problems with Application to MRI Reconstruction

    Y. Hu, A. Peng, W. Gan, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 12, pp. 776–786, 2026

  • AI-Powered Gradient Echo Plural Contrast Imaging (AI-GEPCI)—A Comprehensive Neurological Protocol From a Single MRI Scan

    J. Lewis, M. S. Goyal, G. F. Wu,

    J. Magn. Reson. Imaging, 2026

  • Dose-aware Diffusion Model for 3D PET Image Denoising: Multi-institutional Validation with Reader Study and Real Low-dose Data

    H. Xie, W. Gan, R. Bayerlein,

    Med. Image Anal., p. 104039, 2026

  • RELD: Regularization by Latent Denoising

    P. Cascarano, L. Stacchio, A. Sebastiani,

    IEEE Signal Process. Lett., vol. 33, pp. 2305–2309, 2026

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  • Integrated quantitative biomarkers of placental texture and hemodynamics improve assessment of pregnancies at risk for adverse fetal outcomes

    A. K. Scott, E. M. Louwagie, E. P. Chandler,

    Placenta, 2026

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  • Moments Matter: Posterior Recovery in Poisson Denoising via Log-Networks

    S. Shoushtari, E. P. Chandler, and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), Barcelona, Spain, 2026

  • Deep Parameter Interpolation for Scalar Conditioning

    C. Y. Park, M. T. McCann, C. Garcia-Cardona, B. Wohlberg, and U. S. Kamilov

    Findings of IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), Denver, CO, USA, 2026

2025

  • Stochastic Deep Restoration Priors for Imaging Inverse Problems

    Y. Hu, A. Peng, W. Gan,

    Int. Conf. Machine Learning (ICML), pp. 24621–24652, Vancouver, Canada, 2025

  • FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems

    M. Terris, U. S. Kamilov, and T. Moreau

    IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), pp. 23185–23194, Nashville, TN, USA, 2025

  • Kernel Density Steering: Inference-Time Scaling via Mode Seeking for Image Restoration

    Y. Hu, K. Mei, M. Sahraee-Ardakan,

    Adv. Neural Information Processing Systems (NeurIPS), San Diego, CA, USA, 2025

  • Random Walks with Tweedie: A Unified View of Score-Based Diffusion Models

    C. Y. Park, M. T. McCann, C. Garcia-Cardona, B. Wohlberg, and U. S. Kamilov

    IEEE Signal Process. Mag., vol. 42, no. 3, pp. 40–51, 2025

  • Closed-Form Approximation of the Total Variation Proximal Operator

    E. P. Chandler, S. Shoushtari, B. Wohlberg, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 11, pp. 1217–1228, 2025

  • CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping

    X. Xu, W. Gan, S. V. V. N. Kothapalli, D. A. Yablonskiy, and U. S. Kamilov

    J. Math. Imaging Vis., vol. 67, no. 20, 2025

  • Efficient Model-Based Deep Learning via Network Pruning and Fine-Tuning

    C. Y. Park, W. Gan, Z. Zou,

    J. Math. Imaging Vis., vol. 67, no. 21, 2025

  • Computational field-resolved coherent chemical imaging

    S. Zhao, L. Chibani, E. Chandler,

    Nat. Commun., vol. 16, no. 7406, 2025

  • Advanced Quantification Pipeline Reveals New Spatial and Temporal Tumor Characteristics in Preclinical Multiple Myeloma

    Z. Sun, J. Godbe, A. Zheleznyak,

    EJNMMI Research, vol. 15, no. 95, 2025

  • Multimodal Diffusion Bridge with Attention-Based SAR Fusion for Satellite Image Cloud Removal

    Y. Hu, S. Lohit, U. S. Kamilov, and T. K. Marks

    IEEE Trans. Geosci. Remote Sens., vol. 63, p. 5639612, 2025

  • Gaussian is All You Need: A Unified Framework for Solving Inverse Problems via Diffusion Posterior Sampling

    N. T. Yismaw, U. S. Kamilov, and M. S. Asif

    IEEE Trans. Comput. Imag., vol. 11, pp. 1020–1030, 2025

  • Pseudo-MRI-Guided PET Image Reconstruction Method Based on a Diffusion Probabilistic Model

    W. Gan, H. Xie, C. von Gall,

    IEEE Trans. Radiat. Plasma Med. Sci., vol. 9, no. 4, pp. 412–420, 2025

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  • CDDIP: Constrained Diffusion-Driven Deep Image Prior for Seismic Data Reconstruction

    P. Goyes-Penafiel, U. S. Kamilov, and H. Arguello

    IEEE Geosci. Remote Sens. Lett., vol. 22, pp. 1–5, 2025

  • Fast motion-compensated reconstruction for 4D-CBCT using deep learning-based groupwise registration

    Z. Zhang, Y. Hao, X. Jin,

    Biomed. Phys. Eng. Express, vol. 11, no. 1, p. 015030, 2025

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  • A generalizable diffusion framework for 3D low-dose and few-view cardiac SPECT imaging

    H. Xie, W. Gan, W. Ji,

    Med. Image Anal., vol. 106, p. 103729, 2025

  • Bioengineering approaches for patient-specific analysis of placenta structure and function

    A. K. Scott, D. M. Fodera, P. Yang,

    Placenta, vol. 166, pp. 154–163, 2025

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  • Plug-and-Play Priors as a Score-Based Method

    C. Y. Park, Y. Hu, M. T. McCann,

    IEEE Int. Conf. Image Proc. (ICIP), pp. 49–54, Anchorage, USA, 2025

  • FLAIR: A Conditional Diffusion Framework with Applications to Face Video Restoration

    Z. Zou, J. Liu, S. Shoushtari,

    IEEE/CVF Wint. Conf. on Appli. of Comp. Vis. (WACV), pp. 5228–5238, Tucson, Arizona, 2025

  • A Self-Supervised Diffusion Bridge for MRI Reconstruction

    H. Gao, W. Gan, Y. Hu, H. An, and U. S. Kamilov

    IEEE Int. Symp. Biomedical Imaging (ISBI), pp. 1–4, Houston, TX, USA, 2025

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  • Plug-and-Play Posterior Sampling for Blind Inverse Problems

    A. Li, W. Gan, and U. S. Kamilov

    IEEE Stat. Signal Process. Workshop (SSP), pp. 81–85, Edinburgh, UK, 2025

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  • Enhancing Seismic Post-stack Reconstruction with Diffusion Models: Addressing Uncertainty and Structural Complexity

    P. Goyes-Peñafiel, H. Arguello, and U. S. Kamilov

    IEEE Stat. Signal Process. Workshop (SSP), pp. 86–90, Edinburgh, UK, 2025

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  • Covariance-Corrected Diffusion Models for Solving Inverse Problems

    N. T. Yismaw, U. S. Kamilov, and M. S. Asif

    IEEE Stat. Signal Process. Workshop (SSP), pp. 26–30, Edinburgh, UK, 2025

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2024

  • Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis

    S. Shoushtari, J. Liu, E. Chandler, M. S. Asif, and U. S. Kamilov

    Int. Conf. Machine Learning (ICML), pp. 45154–45182, Vienna, Austria, 2024

  • A Restoration Network as an Implicit Prior

    Y. Hu, M. Delbracio, P. Milanfar, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), Vienna, Austria, 2024

  • A Plug-and-Play Image Registration Network

    J. Hu, W. Gan, Z. Sun, H. An, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), Vienna, Austria, 2024

  • Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models

    M. Renaud, J. Liu, V. de Bortoli, A. Almansa, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), Vienna, Austria, 2024

  • SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction

    Y. Hu, W. Gan, C. Ying,

    Magn. Reson. Med., vol. 92, no. 3, pp. 1048–1063, 2024

  • PtychoDV: Vision Transformer-Based Deep Unrolling Network for Ptychographic Image Reconstruction

    W. Gan, Q. Zhai, M. T. McCann,

    IEEE Open J. Signal Process., vol. 5, pp. 539–547, 2024

  • Domain Expansion via Network Adaptation for Solving Inverse Problems

    N. Yismaw, U. S. Kamilov, and M. S. Asif

    IEEE Trans. Comput. Imag., vol. 10, pp. 549–559, 2024

  • Constrained Regularization by Denoising With Automatic Parameter Selection

    P. Cascarano, A. Benfenati, U. S. Kamilov, and X. Xu

    IEEE Signal Process. Lett., vol. 31, pp. 556–560, 2024

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  • DiffGEPCI: 3D MRI Synthesis from mGRE Signals using 2.5D Diffusion Model

    Y. Hu, S. V. V. N. Kothapalli, W. Gan,

    IEEE Int. Symp. Biomedical Imaging (ISBI), pp. 1–4, Athens, Greece, 2024

2023

  • Block Coordinate Plug-and-Play Methods for Blind Inverse Problems

    W. Gan, S. Shoushtari, Y. Hu,

    Adv. Neural Information Processing Systems (NeurIPS), pp. 78607–78620, New Orleans, USA, 2023

  • Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

    S. Hurault, U. S. Kamilov, A. Leclaire, and N. Papadakis

    Adv. Neural Information Processing Systems (NeurIPS), pp. 27251–27280, New Orleans, USA, 2023

  • DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstruction

    J. Liu, R. Anirudh, J. J. Thiagarajan,

    IEEE Int. Conf. Comp. Vis. (ICCV), pp. 10498–10508, Paris, France, 2023

  • Plug-and-Play Methods for Integrating Physical and Learned Models in Computational Imaging

    U. S. Kamilov, C. A. Bouman, G. T. Buzzard, and B. Wohlberg

    IEEE Signal Process. Mag., vol. 40, no. 1, pp. 85–97, 2023

  • Deep Equilibrium Learning of Explicit Regularizers for Imaging Inverse Problems

    Z. Zou, J. Liu, B. Wohlberg, and U. S. Kamilov

    IEEE Open J. Signal Process., vol. 4, pp. 390–398, 2023

  • Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees

    W. Gan, C. Ying, P. Eshraghi,

    IEEE Trans. Comput. Imag., vol. 4, pp. 796–807, 2023

  • Respiratory motion management using a single rapid MRI scan for a 0.35 T MRI-Linac system

    S. Chen, C. Eldeniz, T. J. Fraum,

    Med. Phys., vol. 50, no. 10, pp. 6163–6176, 2023

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  • Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach

    P. Goyes-Penafiel, E. Vargas, C. V. Correa,

    IEEE Trans. Geosci. Remote Sens., vol. 61, pp. 1–12, 2023

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  • Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties

    S. Kahali, S. V. V. N. Kothapalli, X. Xu, U. S. Kamilov, and D. Yablonskiy

    NMR Biomed., vol. 36, no. 5, p. e4883, 2023

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  • Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction

    Z. Zhang, J. Liu, D. Yang, U. S. Kamilov, and G. Hugo

    Med. Phys., vol. 50, no. 2, pp. 808–820, 2023

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  • Overcoming Distribution Shifts in Plug-And-Play Methods With Test-Time Training★

    C. Park, S. Shoushtari, W. Gan, and U. S. Kamilov

    IEEE Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), pp. 511–515, Los Sueños, Costa Rica, 2023

    CAMSAP 2023 Student Paper Award finalist

  • Convergence of Nonconvex PnP-ADMM With MMSE Denoisers

    E. P. Chandler, S. Shoushtari, J. Liu, M. S. Asif, and U. S. Kamilov

    IEEE Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), pp. 511–515, Los Sueños, Costa Rica, 2023

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  • Diffusion Models for Phase Retrieval in Computational Imaging

    S. Shoushtari, J. Liu, and U. S. Kamilov

    57th Asilomar Conf. Signals, Systems, & Computers, Pacific Grove, CA, 2023

  • Dual-Cycle: Self-Supervised Dual-View Fluorescence Microscopy Image Reconstruction using CycleGAN

    T. Kerepecky, J. Liu, X. W. Ng, D. W. Piston, and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), Rhodes Island, Greece, 2023

  • Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model

    J. Hu, S. Shoushtari, Z. Zou,

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), Rhodes Island, Greece, 2023

  • SINCO: A Novel structural regularizer for image compression using implicit neural representations

    W. Gan, H. Gao, Z. Sun, and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), Rhodes Island, Greece, 2023

2022

  • Online Deep Equilibrium Learning for Regularization by Denoising

    J. Liu, X. Xu, W. Gan, and U. S. Kamilov

    Adv. Neural Information Processing Systems (NeurIPS), New Orleans, USA, 2022

  • Learning Cross-Video Neural Representations for High-Quality Frame Interpolation

    W. Shangguan, Y. Sun, W. Gan, and U. S. Kamilov

    European Conference on Computer Vision (ECCV), pp. 511–528, Tel Aviv, Israel, 2022

  • Deep Model-Based Architectures for Inverse Problems under Mismatched Priors

    S. Shoushtari, J. Liu, Y. Hu, and U. S. Kamilov

    IEEE J. Sel. Areas Inf. Theory, vol. 3, no. 3, pp. 468–480, 2022

  • Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields

    R. Liu, Y. Sun, J. Zhu, L. Tian, and U. S. Kamilov

    Nat. Mach. Intell., vol. 4, pp. 781–791, 2022

  • Deformation-Compensated Learning for Image Reconstruction without Ground Truth

    W. Gan, Y. Sun, C. Eldeniz, H. An, and U. S. Kamilov

    IEEE Trans. Med. Imag., vol. 41, no. 9, pp. 2371–2384, 2022

  • Learning-based Motion Artifact Removal Networks for Quantitative R2* Mapping

    X. Xu, S. V. V. N. Kothapalli, J. Liu,

    Magn. Reson. Med., vol. 88, no. 1, pp. 106–119, 2022

  • MR-Assisted PET Respiratory Motion Correction Using Deep-Learning Based Short-Scan Motion Fields

    S. Chen, T. J. Fraum, C. Eldeniz,

    Magn. Reson. Med., vol. 88, no. 2, pp. 676–690, 2022

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  • Estimation of the mechanical properties of a transversely isotropic material from shear wave fields via artificial neural networks

    Z. Hou, C. A. Guertler, R. J. Okamoto,

    J. Mech. Behav. Biomed. Mater., vol. 126, p. 105046, 2022

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  • Monotonically Convergent Regularization by Denoising

    Y. Hu, J. Liu, X. Xu, and U. S. Kamilov

    IEEE Int. Conf. Image Proc. (ICIP), pp. 426–430, Bordeaux, France, 2022

  • Bregman Plug-and-Play Priors

    A. H. Al-Shabili, X. Xu, I. Selesnick, and U. S. Kamilov

    IEEE Int. Conf. Image Proc. (ICIP), pp. 241–245, Bordeaux, France, 2022

2021

  • Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition

    J. Liu, S. Asif, B. Wohlberg, and U. S. Kamilov

    Adv. Neural Information Processing Systems (NeurIPS), 2021

  • Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors★

    Y. Sun, J. Liu, Y. Sun, B. Wohlberg, and U. S. Kamilov

    Int. Conf. Learn. Represent. (ICLR), 2021

    Spotlight (top 4% of papers)

  • CoIL: Coordinate-based Internal Learning for Tomographic Imaging

    Y. Sun, J. Liu, M. Xie, B. Wohlberg, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 7, pp. 1400–1412, 2021

  • Scalable Plug-and-Play ADMM with Convergence Guarantees

    Y. Sun, Z. Wu, X. Xu, B. Wohlberg, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 7, pp. 849–863, 2021

  • SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees

    J. Liu, Y. Sun, W. Gan,

    IEEE Trans. Comput. Imag., vol. 7, pp. 598–610, 2021

  • Phase2Phase: Respiratory Motion-Resolved Reconstruction of Free-Breathing Magnetic Resonance Imaging Using Deep Learning Without a Ground Truth for Improved Liver Imaging

    C. Eldeniz, W. Gan, S. Chen,

    Invest. Radiol., vol. 56, no. 12, pp. 809–819, 2021

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  • Joint Reconstruction and Calibration using Regularization by Denoising

    M. Xie, J. Liu, B. Wohlberg, and U. S. Kamilov

    IEEE Int. Conf. Comp. Vis. Workshops (ICCVW), pp. 4028–4037, 2021

  • Self-Supervised Joint Image Reconstruction and Coil Sensitivity Calibration in Parallel MRI without Ground Truth

    W. Gan, Y. Hu, C. Eldeniz,

    IEEE Int. Conf. Comp. Vis. Workshops (ICCVW), pp. 4048–4056, 2021

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  • Stochastic Deep Unfolding for Imaging Inverse Problems

    J. Liu, Y. Sun, W. Gan,

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 1395–1399, Toronto, Canada, 2021

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  • Deep Image Reconstruction using Unregistered Measurements without Groundtruth

    W. Gan, Y. Sun, C. Eldeniz, H. An, and U. S. Kamilov

    IEEE Int. Symp. Biomedical Imaging 2021 (ISBI), pp. 1531–1534, Nice, France, 2021

2020

  • SIMBA: Scalable Inversion in Optical Tomography using Deep Denoising Priors

    Z. Wu, Y. Sun, A. Matlock,

    IEEE J. Sel. Topics Signal Process., vol. 14, no. 6, pp. 1163–1175, 2020

  • RARE: Image Reconstruction using Deep Priors Learned without Ground Truth

    J. Liu, Y. Sun, C. Eldeniz,

    IEEE J. Sel. Topics Signal Process., vol. 14, no. 6, pp. 1088–1099, 2020

  • Deep learning using a biophysical model for Robust and Accelerated Reconstruction (RoAR) of quantitative and artifact-free R2* images

    M. Torop, S. Kothapalli, Y. Sun,

    Magn. Reson. Med., vol. 84, no. 6, pp. 2932–2942, 2020

  • Block Coordinate Regularization by Denoising

    Y. Sun, J. Liu, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 6, pp. 908–921, 2020

  • Provable Convergence of Plug-and-Play Priors with MMSE denoisers

    X. Xu, Y. Sun, J. Liu, B. Wohlberg, and U. S. Kamilov

    IEEE Signal Process. Lett., vol. 27, pp. 1280–1284, 2020

  • A New Recurrent Plug-and-Play Prior Based on the Multiple Self-Similarity Network

    G. Song, Y. Sun, J. Liu, Z. Wang, and U. S. Kamilov

    IEEE Signal Process. Lett., vol. 27, pp. 451–455, 2020

  • Boosting the Performance of Plug-and-Play Priors via Denoiser Scaling

    X. Xu, J. Liu, Y. Sun, B. Wohlberg, and U. S. Kamilov

    54th Asilomar Conf. Signals, Systems, & Computers, pp. 1305–1312, Pacific Grove, CA, 2020

  • Image reconstruction for MRI using deep CNN priors trained without ground truth

    W. Gan, C. Eldeniz, J. Liu, H. An, and U. S. Kamilov

    54th Asilomar Conf. Signals, Systems, & Computers, pp. 475–479, Pacific Grove, CA, 2020

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2019

  • Block Coordinate Regularization by Denoising

    Y. Sun, J. Liu, and U. S. Kamilov

    Adv. Neural Information Processing Systems (NeurIPS), pp. 382–392, Vancouver, Canada, 2019

  • An Online Plug-and-Play Algorithm for Regularized Image Reconstruction

    Y. Sun, B. Wohlberg, and U. S. Kamilov

    IEEE Trans. Comput. Imag., vol. 5, no. 3, pp. 395–408, 2019

  • Holographic particle localization under multiple scattering

    W. Tahir, U. S. Kamilov, and L. Tian

    SPIE Adv. Photon., vol. 1, no. 3, p. 036003, 2019

  • Infusing Learned Priors into Model-Based Multispectral Imaging

    J. Liu, Y. Sun, and U. S. Kamilov

    IEEE 8th Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), Guadeloupe, France, 2019

  • Online Regularization by Denoising with Applications to Phase Retrieval

    Z. Wu, Y. Sun, J. Liu, and U. S. Kamilov

    IEEE Int. Conf. Comp. Vis. Workshops (ICCVW), pp. 3887–3895, Seoul, South Korea, 2019

  • Plug-and-Play Priors for Reconstruction-based Placental Image Registration

    J. Xing, U. S. Kamilov, W. Wu, Y. Wang, and M. Zhang

    Medical Image Computing and Computer-Assisted Intervention Workshops (MICCAIW), pp. 133–142, Shenzhen, China, 2019

  • Regularized Fourier Ptychography using an Online Plug-and-Play Algorithm

    Y. Sun, S. Xu, Y. Li,

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 7665–7669, Brighton, UK, 2019

  • Image Restoration using Total Variation Regularized Deep Image Prior

    J. Liu, Y. Sun, X. Xu, and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 7715–7719, Brighton, UK, 2019

  • signProx: One-Bit Proximal Algorithm for Nonconvex Stochastic Optimization

    X. Xu and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 7800–7804, Brighton, UK, 2019

  • Plug-In Stochastic Gradient Method

    Y. Sun, B. Wohlberg, and U. S. Kamilov

    International Biomedical and Astronomical Signal Processing Frontiers Workshop (BASP), p. 75, Villars-sur-Ollon, Switzerland, 2019

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2018

  • Sparse Blind Deconvolution for Distributed Radar Autofocus Imaging

    H. Mansour, D. Liu, U. S. Kamilov, and P. T. Boufounos

    IEEE Trans. Comput. Imag., vol. 4, no. 4, pp. 537–551, 2018

  • Learning-based Image Reconstruction via Parallel Proximal Algorithm

    E. Bostan, U. S. Kamilov, and L. Waller

    IEEE Signal Process. Lett., vol. 25, no. 7, pp. 989–993, 2018

  • Efficient and accurate inversion of multiple scattering with deep learning

    Y. Sun, Z. Xia, and U. S. Kamilov

    Opt. Express, vol. 26, no. 11, pp. 14678–14688, 2018

  • SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering

    H.-Y. Liu, D. Liu, H. Mansour,

    IEEE Trans. Comput. Imag., vol. 4, no. 1, pp. 73–86, 2018

  • Stability of Scattering Decoder For Nonlinear Diffractive Imaging

    Y. Sun and U. S. Kamilov

    4th International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST), p. 31, Marseille, France, 2018

  • Robust sensor localization based on Euclidean distance matrix

    D. Liu, H. Mansour, P. T. Boufounos, and U. S. Kamilov

    IEEE Int. Geosci. Remote Sensing Symp. (IGARSS), pp. 7998–8001, Valencia, Spain, 2018

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  • Nonconvex optimization for diffractive imaging

    Y. Ma, H. Mansour, D. Liu, P. T. Boufounos, and U. S. Kamilov

    OSA Mathematics in Imaging (MATH), p. MW5D.3, Orlando, FL, 2018

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  • Sampling and processing for multiple scattering in inline compressive holography

    W. Tahir, U. S. Kamilov, and L. Tian

    OSA Applications of Lasers for Sensing and Free Space Communications (LS&C), p. JTh3B.1, Orlando, FL, 2018

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  • Radar Autofocus using Sparse Blind Deconvolution

    H. Mansour, U. S. Kamilov, D. Liu, and P. T. Boufounos

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 1623–1627, Calgary, Canada, 2018

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  • DeepCASD: An End-to-End Approach for Multi-spectral Image Super-Resolution

    B. Wen, U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 6503–6507, Calgary, Canada, 2018

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  • Accelerated Image Reconstruction for Nonlinear Diffractive Imaging

    Y. Ma, H. Mansour, D. Liu, P. T. Boufounos, and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 6473–6477, Calgary, Canada, 2018

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2017

  • A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems

    U. S. Kamilov, H. Mansour, and B. Wohlberg

    IEEE Signal Process. Lett., vol. 24, no. 12, pp. 1872–1876, 2017

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  • Motion-Adaptive Depth Superresolution

    U. S. Kamilov and P. T. Boufounos

    IEEE Trans. Image Process., vol. 26, no. 4, pp. 1723–1731, 2017

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  • A Parallel Proximal Algorithm for Anisotropic Total Variation Minimization

    U. S. Kamilov

    IEEE Trans. Image Process., vol. 26, no. 2, pp. 539–548, 2017

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  • Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

    S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov

    IEEE Trans. Inf. Theory., vol. 63, no. 1, pp. 676–697, 2017

  • Online Convolutional Dictionary Learning for Multimodal Imaging

    K. Degraux, U. S. Kamilov, P. T. Boufounos, and D. Liu

    IEEE Int. Conf. Image Proc. (ICIP), pp. 1617–1621, Beijing, China, 2017

  • Fusion of multi-angular aerial Images based on epipolar geometry and matrix completion

    Y. Ma, D. Liu, H. Mansour,

    IEEE Int. Conf. Image Proc. (ICIP), pp. 1197–1201, Beijing, China, 2017

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  • Learning Convolutional Proximal Filters

    U. S. Kamilov, H. Mansour, and D. Liu

    7th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS), p. 101, Lisbon, Portugal, 2017

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  • A Kaczmarz Method for Low Rank Matrix Recovery

    H. Mansour, U. S. Kamilov, and O. Yilmaz

    7th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS), p. 60, Lisbon, Portugal, 2017

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  • Compressive Imaging with Iterative Forward Models★

    H.-Y. Liu, U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 6025–6029, New Orleans, LA, 2017

    ICASSP 2017 Student Paper Award finalist

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  • Optical Tomography based on a Nonlinear Model that Handles Multiple Scattering

    M. H. Shoreh, A. Goy, J. Lim,

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 6220–6224, New Orleans, LA, 2017

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  • Learning Bayesian Optimal FISTA with Error Backpropagation

    U. S. Kamilov and H. Mansour

    International Biomedical and Astronomical Signal Processing Frontiers Workshop (BASP), p. 66, Villars-sur-Ollon, Switzerland, 2017

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2016

  • A Recursive Born Approach to Nonlinear Inverse Scattering

    U. S. Kamilov, D. Liu, H. Mansour, and P. T. Boufounos

    IEEE Signal Process. Lett., vol. 23, no. 8, pp. 1052–1056, 2016

  • Learning optimal nonlinearities for iterative thresholding algorithms

    U. S. Kamilov and H. Mansour

    IEEE Signal Process. Lett., vol. 23, no. 5, pp. 747–751, 2016

  • Optical tomographic image reconstruction based on beam propagation and sparse regularization

    U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh,

    IEEE Trans. Comput. Imag., vol. 2, no. 1, pp. 59–70, 2016

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  • Compressive Tomographic Radar Imaging with Total Variation Regularization

    D. Liu, U. S. Kamilov, and P. T. Boufounos

    IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), pp. 120–123, Aachen, Germany, 2016

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  • Coherent Distributed Array Imaging under Unknown Position Perturbations

    D. Liu, U. S. Kamilov, and P. T. Boufounos

    IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), pp. 105–109, Aachen, Germany, 2016

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  • Online Blind Deconvolution for Sequential Through-the-Wall-Radar-Imaging

    H. Mansour, U. S. Kamilov, D. Liu,

    IEEE 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar, and Remote Sensing (CoSeRa), pp. 61–65, Aachen, Germany, 2016

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  • Learning MMSE Optimal Thresholds for FISTA

    U. S. Kamilov and H. Mansour

    3rd International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST), p. 42, Aalborg, Denmark, 2016

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  • Minimizing Isotropic Total Variation without Subiterations

    U. S. Kamilov

    3rd International Traveling Workshop on Interactions between Sparse models and Technology (iTWIST), p. 39, Aalborg, Denmark, 2016

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  • Depth Superresolution using Motion Adaptive Regularization

    U. S. Kamilov and P. T. Boufounos

    IEEE Int. Conf. Multimedia & Expo Workshops (ICMEW), pp. 1–6, Seattle, WA, 2016

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  • Parallel proximal methods for total variation minimization

    U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 4697–4701, Shanghai, China, 2016

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  • Autocalibration of Lidar and Optical Cameras via Edge Alignment

    J. Castorena, U. S. Kamilov, and P. T. Boufounos

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 2862–2866, Shanghai, China, 2016

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  • Multipath Removal by Online Blind Deconvolution in Through-the-Wall-Imaging

    H. Mansour and U. S. Kamilov

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 3106–3110, Shanghai, China, 2016

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2015

  • Learning Approach to Optical Tomography★

    U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh,

    Optica, vol. 2, no. 6, pp. 517–522, 2015

    Featured in Nature "News & Views" (vol. 523, pp. 416-416)

  • Isotropic inverse-problem approach for two-dimensional phase unwrapping

    U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, D. Psaltis, and M. Unser

    J. Opt. Soc. Am. A, vol. 32, no. 6, pp. 1092–1100, 2015

  • Extended Target Localization with Total-Variation Denoising in Through-the-Wall-Imaging

    H. Handa, H. Mansour, D. Liu, and U. S. Kamilov

    IEEE Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), pp. 445–448, Cancun, Mexico, 2015

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  • Sparsity-Driven Distributed Array Imaging

    D. Liu, U. S. Kamilov, and P. T. Boufounos

    IEEE Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), pp. 441–444, Cancun, Mexico, 2015

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  • Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization

    S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov

    IEEE Int. Symp. Inform. Theory (ISIT), pp. 1640–1644, Hong Kong, 2015

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2014

  • Variational Justification of Cycle Spinning for Wavelet-Based Solutions of Inverse Problems

    U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Signal Process. Lett., vol. 21, no. 11, pp. 1326–1330, 2014

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  • Approximate Message Passing with Consistent Parameter Estimation and Application to Sparse Learning

    U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser

    IEEE Trans. Inf. Theory, vol. 60, no. 5, pp. 2969–2985, 2014

2013

  • Sparse Stochastic Processes and Discretization of Linear Inverse Problems

    E. Bostan, U. S. Kamilov, M. Nilchian, and M. Unser

    IEEE Trans. Image Process., vol. 22, no. 7, pp. 2699–2710, 2013

  • Bayesian Denoising: From MAP to MMSE Using Consistent Cycle Spinning

    A. Kazerouni, U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Signal Process. Lett., vol. 20, no. 3, pp. 249–252, 2013

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  • Bayesian Estimation for Continuous-Time Sparse Stochastic Processes

    A. Amini, U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Trans. Signal Process., vol. 61, no. 4, pp. 907–920, 2013

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  • MMSE Estimation of Sparse Levy Processes

    U. S. Kamilov, P. Pad, A. Amini, and M. Unser

    IEEE Trans. Signal Process., vol. 61, no. 1, pp. 137–147, 2013

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  • Sparse Image Deconvolution with Message Passing

    U. S. Kamilov, A. Bourquard, and M. Unser

    Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS), Lausanne, Switzerland, 2013

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  • Consistent Discretization of Linear Inverse Problems using Sparse Stochastic Processes

    E. Bostan, U. S. Kamilov, M. Nilchian, and M. Unser

    Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS), Lausanne, Switzerland, 2013

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  • MAP Estimators for Self-Similar Sparse Stochastic Models

    E. Bostan, J. Fageot, U. S. Kamilov, and M. Unser

    International Conference on Sampling Theory and Applications (SAMPTA), pp. 197–199, Bremen, Germany, 2013

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  • Autocalibrated Signal Reconstruction from Linear Measurements using Adaptive GAMP

    U. S. Kamilov, A. Bourquard, E. Bostan, and M. Unser

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 197–199, Vancouver, Canada, 2013

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  • Benefits of Consistency in Image Denoising with Steerable Wavelets

    B. Tekin, U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 1355–1358, Vancouver, Canada, 2013

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2012

  • Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning

    U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser

    Adv. Neural Information Processing Systems (NeurIPS), pp. 2447–2455, Lake Tahoe, NV, 2012

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  • Message-Passing De-Quantization with Applications to Compressed Sensing★

    U. S. Kamilov, V. K. Goyal, and S. Rangan

    IEEE Trans. Signal Process., vol. 60, no. 12, pp. 6270–6281, 2012

    IEEE Signal Processing Society Best Paper Award 2017

  • One-Bit Measurements with Adaptive Thresholds

    U. S. Kamilov, A. Bourquard, A. Amini, and M. Unser

    IEEE Signal Process. Lett., vol. 19, no. 10, pp. 607–610, 2012

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  • Wavelet Shrinkage with Consistent Cycle Spinning Generalizes Total Variation Denoising

    U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Signal Process. Lett., vol. 19, no. 4, pp. 187–190, 2012

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  • The Analog Formulation of Sparsity Implies Infinite Divisibility and Rules Out Bernoulli-Gaussian Priors

    A. Amini, U. S. Kamilov, and M. Unser

    IEEE Information Theory Workshop (ITW), pp. 687–691, Lausanne, Switzerland, 2012

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  • Reconstruction of Biomedical Images and Sparse Stochastic Modeling

    E. Bostan, U. S. Kamilov, and M. Unser

    IEEE Int. Symp. Biomedical Imaging (ISBI), pp. 880–883, Barcelona, Spain, 2012

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  • MMSE Denoising of Sparse Lévy Processes via Message Passing

    U. S. Kamilov, A. Amini, and M. Unser

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 3637–3640, Kyoto, Japan, 2012

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  • Generalized Total Variation Denoising via Augmented Lagrangian Cycle Spinning with Haar Wavelets

    U. S. Kamilov, E. Bostan, and M. Unser

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 909–912, Kyoto, Japan, 2012

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  • Bayesian Denoising of Generalized Poisson Processes with Finite Rate of Innovation

    A. Amini, U. S. Kamilov, and M. Unser

    IEEE Int. Conf. Acoustics, Speech and Signal Process. (ICASSP), pp. 3629–3632, Kyoto, Japan, 2012

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2011

  • Generalized Approximate Message Passing Estimation from Quantized Samples★

    U. S. Kamilov, V. K. Goyal, and S. Rangan

    IEEE 4th Int. Workshop on Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP), pp. 401–404, San Juan, Puerto Rico, 2011

    CAMSAP 2011 Student Paper Award finalist

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  • Message-Passing Estimation from Quantized Samples

    U. S. Kamilov, V. K. Goyal, and S. Rangan

    4th Workshop on Signal Process. with Adaptive Sparse Structured Representations (SPARS), p. 58, Edinburgh, UK, 2011

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  • Optimal Quantization for Compressive Sensing under Message Passing Reconstruction

    U. S. Kamilov, V. K. Goyal, and S. Rangan

    IEEE Int. Symp. Inform. Theory (ISIT), pp. 390–394, Saint-Petersburg, Russia, 2011

Theses