Junqi Tang - RankMe

46 papers A* 4Misc 3Journal 36Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A New Convergence Analysis of Plug-and-Play Proximal Gradient Descent Under Prior Mismatch. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2026	J	`jnl`	A deep learning framework for aviation risk classification and high-order coupled risk modeling. Reliab. Eng. Syst. Saf. Xirui Li, Fairuz Izzuddin Romli, Syaril Azrad Md Ali, Amzari Zhahir, Junqi Tang
2026	A*	`conf`	Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. AAAI Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2026	J	`jnl`	Domain-adapted deep learning for aviation incident classification with multiple labels and risk assessment. Eng. Appl. Artif. Intell. Xirui Li, Fairuz Izzuddin Romli, Syaril Azrad Md Ali, Amzari Zhahir, Junqi Tang
2026	J	`jnl`	The Practicality of Normalizing Flow Test-Time Training in Bayesian Inference for Agent-Based Models. CoRR Junyao Zhang, Jinglai Li, Junqi Tang
2025	J	`jnl`	Fast Equivariant Imaging: Acceleration for Unsupervised Learning via Augmented Lagrangian and Auxiliary PnP Denoisers. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2025	J	`jnl`	From Image Denoisers to Regularizing Imaging Inverse Problems: An Overview. CoRR Hong Ye Tan, Subhadip Mukherjee, Junqi Tang
2025	Misc	`conf`	Iterative Operator Sketching Framework for Large-Scale Imaging Inverse Problems. ICASSP Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2025	J	`jnl`	Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Linear Inverse Problems. J. Math. Imaging Vis. Junqi Tang, Guixian Xu, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2025	—	`conf`	Stochastic Primal-Dual Three Operator Splitting Algorithm with Extension to Equivariant Regularization-by-Denoising. SSVM (2) Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2024	J	`jnl`	A Guide to Stochastic Optimisation for Large-Scale Inverse Problems. CoRR Matthias J. Ehrhardt, Zeljko Kereta, Jingwei Liang, Junqi Tang
2024	J	`jnl`	Blessing of Dimensionality for Approximating Sobolev Classes on Manifolds. CoRR Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration. Trans. Mach. Learn. Res. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	NF-ULA: Normalizing Flow-Based Unadjusted Langevin Algorithm for Imaging Inverse Problems. SIAM J. Imaging Sci. Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2024	J	`jnl`	Practical Acceleration of the Condat-Vũ Algorithm. SIAM J. Imaging Sci. Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang
2024	J	`jnl`	Provably Convergent Plug-and-Play Quasi-Newton Methods. SIAM J. Imaging Sci. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Sketched Equivariant Imaging Regularization and Deep Internal Learning for Inverse Problems. CoRR Guixian Xu, Jinglai Li, Junqi Tang
2024	J	`jnl`	Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes. J. Math. Imaging Vis. Antonin Chambolle, Claire Delplancke, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. CoRR Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2024	J	`jnl`	Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation. Trans. Mach. Learn. Res. Hong Ye Tan, Ziruo Cai, Marcelo Pereyra, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Data-Driven Mirror Descent with Input-Convex Neural Networks. SIAM J. Math. Data Sci. Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	J	`jnl`	Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems. CoRR Qingping Zhou, Jiayu Qian, Junqi Tang, Jinglai Li
2023	J	`jnl`	NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems. CoRR Ziruo Cai, Junqi Tang, Subhadip Mukherjee, Jinglai Li, Carola-Bibiane Schönlieb, Xiaoqun Zhang
2023	J	`jnl`	OsmoticGate: Adaptive Edge-Based Real-Time Video Analytics for the Internet of Things. IEEE Trans. Computers Bin Qian, Zhenyu Wen, Junqi Tang, Ye Yuan, Albert Y. Zomaya, Rajiv Ranjan
2023	J	`jnl`	Provably Convergent Plug-and-Play Quasi-Newton Methods. CoRR Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb
2023	Misc	`conf`	Robust Data-Driven Accelerated Mirror Descent. ICASSP Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Andreas Hauptmann, Carola-Bibiane Schönlieb
2023	J	`jnl`	Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging. CoRR Marcello Carioni, Subhadip Mukherjee, Hong Ye Tan, Junqi Tang
2022	J	`jnl`	Accelerating Deep Unrolling Networks via Dimensionality Reduction. CoRR Junqi Tang, Subhadip Mukherjee, Carola-Bibiane Schönlieb
2022	J	`jnl`	Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients. CoRR Junqi Tang
2022	J	`jnl`	Data-Consistent Local Superresolution for Medical Imaging. CoRR Junqi Tang
2022	J	`jnl`	Equivariance Regularization for Image Reconstruction. CoRR Junqi Tang
2022	J	`jnl`	Operator Sketching for Deep Unrolling Networks. CoRR Junqi Tang
2022	J	`jnl`	Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning. CoRR Junqi Tang, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb
2021	J	`jnl`	A Stochastic Proximal Alternating Minimization for Nonsmooth and Nonconvex Optimization. SIAM J. Imaging Sci. Derek Driggs, Junqi Tang, Jingwei Liang, Mike E. Davies, Carola-Bibiane Schönlieb
2021	J	`jnl`	Stochastic Primal-Dual Deep Unrolling Networks for Imaging Inverse Problems. CoRR Junqi Tang
2021	A*	`conf`	The Neural Tangent Link Between CNN Denoisers and Non-Local Filters. CVPR Julián Tachella, Junqi Tang, Mike E. Davies
2020	J	`jnl`	A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems. CoRR Junqi Tang, Mike E. Davies
2020	J	`jnl`	CNN Denoisers as Non-Local Filters: The Neural Tangent Denoiser. CoRR Julián Tachella, Junqi Tang, Mike E. Davies
2020	J	`jnl`	The Practicality of Stochastic Optimization in Imaging Inverse Problems. IEEE Trans. Computational Imaging Junqi Tang, Karen O. Egiazarian, Mohammad Golbabaee, Mike E. Davies
2019	—	`—`	Randomized structure-adaptive optimization. Junqi Tang
2019	Misc	`conf`	The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems. ICASSP Junqi Tang, Karen O. Egiazarian, Mike E. Davies
2019	J	`jnl`	The Practicality of Stochastic Optimization in Imaging Inverse Problems. CoRR Junqi Tang, Karen O. Egiazarian, Mohammad Golbabaee, Mike E. Davies
2018	A*	`conf`	Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes. NeurIPS Junqi Tang, Mohammad Golbabaee, Francis R. Bach, Mike E. Davies
2017	—	`conf`	Exploiting the structure via sketched gradient algorithms. GlobalSIP Junqi Tang, Mohammad Golbabaee, Mike E. Davies
2017	A*	`conf`	Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares. ICML Junqi Tang, Mohammad Golbabaee, Mike E. Davies
2016	J	`jnl`	The Non-uniform Fast Fourier Transform in Computed Tomography. CoRR Junqi Tang