Junqi Tang

CoRR, January, 2026

The Practicality of Normalizing Flow Test-Time Training in Bayesian Inference for Agent-Based Models.

[BibT_eX]

[DOI]

Junyao Zhang

CoRR, January, 2026

A deep learning framework for aviation risk classification and high-order coupled risk modeling.

[BibT_eX]

[DOI]

Xirui Li

Fairuz Izzuddin Romli

Syaril Azrad Md Ali

Amzari Zhahir

Reliab. Eng. Syst. Saf., 2026

Domain-adapted deep learning for aviation incident classification with multiple labels and risk assessment.

[BibT_eX]

[DOI]

Xirui Li

Fairuz Izzuddin Romli

Syaril Azrad Md Ali

Amzari Zhahir

Eng. Appl. Artif. Intell., 2026

Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

From Image Denoisers to Regularizing Imaging Inverse Problems: An Overview.

[BibT_eX]

[DOI]

CoRR, September, 2025

Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Linear Inverse Problems.

[BibT_eX]

[DOI]

J. Math. Imaging Vis., August, 2025

Fast Equivariant Imaging: Acceleration for Unsupervised Learning via Augmented Lagrangian and Auxiliary PnP Denoisers.

[BibT_eX]

[DOI]

CoRR, July, 2025

Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising.

[BibT_eX]

[DOI]

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2025

Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems.

[BibT_eX]

[DOI]

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024

Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes.

[BibT_eX]

[DOI]

Antonin Chambolle

Claire Delplancke

J. Math. Imaging Vis., June, 2024

Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Provably Convergent Plug-and-Play Quasi-Newton Methods.

[BibT_eX]

[DOI]

SIAM J. Imaging Sci., 2024

Practical Acceleration of the Condat-Vũ Algorithm.

[BibT_eX]

[DOI]

Derek Driggs

SIAM J. Imaging Sci., 2024

NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems.

[BibT_eX]

[DOI]

Xiaoqun Zhang

SIAM J. Imaging Sci., 2024

Sketched Equivariant Imaging Regularization and Deep Internal Learning for Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2024

A Guide to Stochastic Optimisation for Large-Scale Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Data-Driven Mirror Descent with Input-Convex Neural Networks.

[BibT_eX]

[DOI]

SIAM J. Math. Data Sci., June, 2023

OsmoticGate: Adaptive Edge-Based Real-Time Video Analytics for the Internet of Things.

[BibT_eX]

[DOI]

IEEE Trans. Computers, April, 2023

Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging.

[BibT_eX]

[DOI]

CoRR, 2023

Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2023

NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems.

[BibT_eX]

[DOI]

Xiaoqun Zhang

CoRR, 2023

Robust Data-Driven Accelerated Mirror Descent.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Accelerating Deep Unrolling Networks via Dimensionality Reduction.

[BibT_eX]

[DOI]

CoRR, 2022

Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning.

[BibT_eX]

[DOI]

CoRR, 2022

Operator Sketching for Deep Unrolling Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients.

[BibT_eX]

[DOI]

CoRR, 2022

Data-Consistent Local Superresolution for Medical Imaging.

[BibT_eX]

[DOI]

CoRR, 2022

Equivariance Regularization for Image Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2022

2021

A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization.

[BibT_eX]

[DOI]

SIAM J. Imaging Sci., 2021

Stochastic Primal-Dual Deep Unrolling Networks for Imaging Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2021

The Neural Tangent Link Between CNN Denoisers and Non-Local Filters.

[BibT_eX]

[DOI]

Julián Tachella

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

The Practicality of Stochastic Optimization in Imaging Inverse Problems.

[BibT_eX]

[DOI]

IEEE Trans. Computational Imaging, 2020

A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2020

CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser.

[BibT_eX]

[DOI]

Julián Tachella

CoRR, 2020

2019

Randomized structure-adaptive optimization.

[BibT_eX]

[DOI]

PhD thesis, 2019

The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems.

[BibT_eX]

[DOI]

Karen O. Egiazarian

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares.

[BibT_eX]

[DOI]

Mohammad Golbabaee

Proceedings of the 34th International Conference on Machine Learning, 2017

Exploiting the structure via sketched gradient algorithms.

[BibT_eX]

[DOI]

Mohammad Golbabaee

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2016

The Non-uniform Fast Fourier Transform in Computed Tomography.

[BibT_eX]

[DOI]