Junqi Tang | DeepAI

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Featured Co-authors

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Julián Tachella
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∙ 07/30/2023

Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems

Combining the strengths of model-based iterative algorithms and data-dri...

0 Qingping Zhou, et al. ∙

∙ 04/17/2023

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

Bayesian methods for solving inverse problems are a powerful alternative...

0 Ziruo Cai, et al. ∙

∙ 03/09/2023

Provably Convergent Plug-and-Play Quasi-Newton Methods

Plug-and-Play (PnP) methods are a class of efficient iterative methods t...

0 Hong Ye Tan, et al. ∙

∙ 08/31/2022

Accelerating Deep Unrolling Networks via Dimensionality Reduction

In this work we propose a new paradigm for designing efficient deep unro...

11 Junqi Tang, et al. ∙

∙ 08/02/2022

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

In this work we propose a stochastic primal-dual preconditioned three-op...

0 Junqi Tang, et al. ∙

∙ 03/21/2022

Operator Sketching for Deep Unrolling Networks

In this work we propose a new paradigm for designing efficient deep unro...

0 Junqi Tang, et al. ∙

∙ 03/14/2022

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

In this work we propose a new paradigm for designing fast plug-and-play ...

0 Junqi Tang, et al. ∙

∙ 02/22/2022

Data-Consistent Local Superresolution for Medical Imaging

In this work we propose a new paradigm of iterative model-based reconstr...

0 Junqi Tang, et al. ∙

∙ 02/10/2022

Equivariance Regularization for Image Reconstruction

In this work, we propose Regularization-by-Equivariance (REV), a novel s...

0 Junqi Tang, et al. ∙

∙ 10/19/2021

Stochastic Primal-Dual Deep Unrolling Networks for Imaging Inverse Problems

In this work we present a new type of efficient deep-unrolling networks ...

0 Junqi Tang, et al. ∙

∙ 06/20/2020

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

In this work we propose an efficient stochastic plug-and-play (PnP) algo...

0 Junqi Tang, et al. ∙

∙ 06/03/2020

CNN Denoisers As Non-Local Filters: The Neural Tangent Denoiser

Convolutional Neural Networks (CNNs) are now a well-established tool for...

0 Julián Tachella, et al. ∙

∙ 10/22/2019

The Practicality of Stochastic Optimization in Imaging Inverse Problems

In this work we investigate the practicality of stochastic gradient desc...

38 Junqi Tang, et al. ∙

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