{"total":186,"rows":[{"id":"2103.12828","title":"Learning to Optimize: A Primer and A Benchmark","created":"2021-03-23","cited_by_count":208,"area":null},{"id":"2102.07944","title":"Deep Equilibrium Architectures for Inverse Problems in Imaging","created":"2021-02-16","cited_by_count":127,"area":null},{"id":"2204.13348","title":"Deep Generalized Unfolding Networks for Image Restoration","created":"2022-04-28","cited_by_count":121,"area":null},{"id":"2110.03220","title":"Gradient Step Denoiser for convergent Plug-and-Play","created":"2021-10-07","cited_by_count":108,"area":null},{"id":"2103.04715","title":"Bayesian imaging using Plug & Play priors: when Langevin meets Tweedie","created":"2021-03-08","cited_by_count":97,"area":null},{"id":"2107.03055","title":"Blind Image Super-Resolution: A Survey and Beyond","created":"2021-07-07","cited_by_count":93,"area":null},{"id":"2201.13256","title":"Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization","created":"2022-01-31","cited_by_count":80,"area":null},{"id":"2301.03362","title":"Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --","created":"2023-01-09","cited_by_count":71,"area":null},{"id":"2203.04845","title":"Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction","created":"2022-03-09","cited_by_count":67,"area":null},{"id":"2205.10102","title":"Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging","created":"2022-05-20","cited_by_count":66,"area":null},{"id":"2310.10835","title":"Provable Probabilistic Imaging using Score-Based Generative Priors","created":"2023-10-16","cited_by_count":51,"area":null},{"id":"2205.02640","title":"Model-Based Deep Learning: On the Intersection of Deep Learning and Optimization","created":"2022-05-05","cited_by_count":50,"area":null},{"id":"2112.00002","title":"Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields","created":"2021-11-27","cited_by_count":48,"area":null},{"id":"2207.06680","title":"Equivariant Hypergraph Diffusion Neural Operators","created":"2022-07-14","cited_by_count":47,"area":null},{"id":"2206.05431","title":"Learned reconstruction methods with convergence guarantees","created":"2022-06-11","cited_by_count":46,"area":null},{"id":"2101.04822","title":"Plug-and-Play Algorithms for Video Snapshot Compressive Imaging","created":"2021-01-13","cited_by_count":42,"area":null},{"id":"2304.11134","title":"Plug-and-Play split Gibbs sampler: embedding deep generative priors in Bayesian inference","created":"2023-04-21","cited_by_count":42,"area":null},{"id":"2211.12461","title":"A Neural-Network-Based Convex Regularizer for Inverse Problems","created":"2022-11-22","cited_by_count":41,"area":null},{"id":"2409.06219","title":"Denoising: A Powerful Building-Block for Imaging, Inverse Problems, and Machine Learning","created":"2024-09-10","cited_by_count":35,"area":null},{"id":"2106.03538","title":"End-to-end reconstruction meets data-driven regularization for inverse problems","created":"2021-06-07","cited_by_count":32,"area":null},{"id":"2109.06548","title":"Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot Compressive Imaging","created":"2021-09-14","cited_by_count":31,"area":null},{"id":"2103.01648","title":"Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior","created":"2021-03-02","cited_by_count":24,"area":null},{"id":"2106.03668","title":"Recovery Analysis for Plug-and-Play Priors using the Restricted Eigenvalue Condition","created":"2021-06-07","cited_by_count":22,"area":null},{"id":"2106.03839","title":"NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results","created":"2021-06-07","cited_by_count":22,"area":null},{"id":"2205.13051","title":"Online Deep Equilibrium Learning for Regularization by Denoising","created":"2022-05-25","cited_by_count":22,"area":null},{"id":"2206.14373","title":"Theoretical Perspectives on Deep Learning Methods in Inverse Problems","created":"2022-06-29","cited_by_count":22,"area":null},{"id":"2209.08240","title":"Deep Plug-and-Play Prior for Hyperspectral Image Restoration","created":"2022-09-17","cited_by_count":22,"area":null},{"id":"2211.06891","title":"Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging","created":"2022-11-13","cited_by_count":22,"area":null},{"id":"2104.06191","title":"Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts","created":"2021-04-13","cited_by_count":21,"area":null},{"id":"2104.10348","title":"Fixed-Point and Objective Convergence of Plug-and-Play Algorithms","created":"2021-04-21","cited_by_count":19,"area":null},{"id":"2109.08879","title":"FastHyMix: Fast and Parameter-free Hyperspectral Image Mixed Noise Removal","created":"2021-09-18","cited_by_count":19,"area":null},{"id":"2101.09379","title":"SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees","created":"2021-01-22","cited_by_count":18,"area":null},{"id":"2104.14090","title":"Feasibility-based Fixed Point Networks","created":"2021-04-29","cited_by_count":17,"area":null},{"id":"2105.08040","title":"Unsupervised Deep Learning Methods for Biological Image Reconstruction and Enhancement","created":"2021-05-17","cited_by_count":17,"area":null},{"id":"2402.01779","title":"Plug-and-Play image restoration with Stochastic deNOising REgularization","created":"2024-02-01","cited_by_count":17,"area":null},{"id":"2303.09040","title":"Hybrid Spectral Denoising Transformer with Guided Attention","created":"2023-03-16","cited_by_count":16,"area":null},{"id":"2303.07271","title":"Provably Convergent Plug-and-Play Quasi-Newton Methods","created":"2023-03-09","cited_by_count":15,"area":null},{"id":"2510.01755","title":"Learning Regularization Functionals for Inverse Problems: A Comparative Study","created":"2025-10-02","cited_by_count":15,"area":null},{"id":"2201.06133","title":"On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent","created":"2022-01-16","cited_by_count":14,"area":null},{"id":"2106.15910","title":"Graph Signal Restoration Using Nested Deep Algorithm Unrolling","created":"2021-06-30","cited_by_count":13,"area":null},{"id":"2109.12880","title":"Wasserstein Patch Prior for Image Superresolution","created":"2021-09-27","cited_by_count":13,"area":null},{"id":"2307.09441","title":"Convergent regularization in inverse problems and linear plug-and-play denoisers","created":"2023-07-18","cited_by_count":13,"area":null},{"id":"2108.01914","title":"An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications to Surface Smoothing and Imaging","created":"2021-08-04","cited_by_count":11,"area":null},{"id":"2301.10155","title":"UNO: Unlimited Sampling Meets One-Bit Quantization","created":"2022-12-10","cited_by_count":11,"area":null},{"id":"2304.11409","title":"The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior","created":"2023-04-22","cited_by_count":11,"area":null},{"id":"2310.00133","title":"Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis","created":"2023-09-29","cited_by_count":11,"area":null},{"id":"2201.08157","title":"WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution","created":"2022-01-20","cited_by_count":10,"area":null},{"id":"2204.10109","title":"Deep Model-Based Super-Resolution with Non-uniform Blur","created":"2022-04-21","cited_by_count":10,"area":null},{"id":"2306.17332","title":"Designing Stable Neural Networks using Convex Analysis and ODEs","created":"2023-06-29","cited_by_count":10,"area":null},{"id":"2309.00066","title":"SoDaCam: Software-defined Cameras via Single-Photon Imaging","created":"2023-08-31","cited_by_count":10,"area":null},{"id":"2402.12292","title":"Regularization by denoising: Bayesian model and Langevin-within-split Gibbs sampling","created":"2024-02-19","cited_by_count":9,"area":null},{"id":"2102.02485","title":"Image Restoration by Deep Projected GSURE","created":"2021-02-04","cited_by_count":8,"area":null},{"id":"2207.13200","title":"Deep Model-Based Architectures for Inverse Problems under Mismatched Priors","created":"2022-07-26","cited_by_count":8,"area":null},{"id":"2301.11525","title":"Mixed Attention Network for Hyperspectral Image Denoising","created":"2023-01-27","cited_by_count":8,"area":null},{"id":"2305.12672","title":"Block Coordinate Plug-and-Play Methods for Blind Inverse Problems","created":"2023-05-22","cited_by_count":8,"area":null},{"id":"2307.12774","title":"Fast Full-frame Video Stabilization with Iterative Optimization","created":"2023-07-24","cited_by_count":8,"area":null},{"id":"2412.16748","title":"Solving Inverse Problems via Diffusion Optimal Control","created":"2024-12-21","cited_by_count":8,"area":null},{"id":"2110.00493","title":"Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration","created":"2021-10-01","cited_by_count":7,"area":null},{"id":"2204.13940","title":"PnP-ReG: Learned Regularizing Gradient for Plug-and-Play Gradient Descent","created":"2022-04-29","cited_by_count":7,"area":null},{"id":"2408.12316","title":"Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video Enhancement","created":"2024-08-22","cited_by_count":7,"area":null},{"id":"2211.00725","title":"LARO: Learned Acquisition and Reconstruction Optimization to accelerate Quantitative Susceptibility Mapping","created":"2022-11-01","cited_by_count":6,"area":null},{"id":"2211.07286","title":"CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature Denoiser","created":"2022-11-14","cited_by_count":6,"area":null},{"id":"2304.14612","title":"Local-Global Transformer Enhanced Unfolding Network for Pan-sharpening","created":"2023-04-28","cited_by_count":6,"area":null},{"id":"2306.17367","title":"Spatially Varying Exposure with 2-by-2 Multiplexing: Optimality and Universality","created":"2023-06-30","cited_by_count":6,"area":null},{"id":"2402.05637","title":"Learning pseudo-contractive denoisers for inverse problems","created":"2024-02-08","cited_by_count":6,"area":null},{"id":"2404.03998","title":"PHISWID: Physics-Inspired Underwater Image Dataset Synthesized from RGB-D Images","created":"2024-04-05","cited_by_count":6,"area":null},{"id":"2404.05001","title":"Dual-Scale Transformer for Large-Scale Single-Pixel Imaging","created":"2024-04-07","cited_by_count":6,"area":null},{"id":"2101.08661","title":"Regularization via deep generative models: an analysis point of view","created":"2021-01-21","cited_by_count":5,"area":null},{"id":"2102.05105","title":"Deep learning architectural designs for super-resolution of noisy images","created":"2021-02-09","cited_by_count":5,"area":null},{"id":"2103.14249","title":"Marine Snow Removal Benchmarking Dataset","created":"2021-03-26","cited_by_count":5,"area":null},{"id":"2201.06931","title":"Deep Equilibrium Models for Video Snapshot Compressive Imaging","created":"2022-01-18","cited_by_count":5,"area":null},{"id":"2205.07770","title":"JR2net: A Joint Non-Linear Representation and Recovery Network for Compressive Spectral Imaging","created":"2022-05-16","cited_by_count":5,"area":null},{"id":"2206.07875","title":"Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training","created":"2022-06-16","cited_by_count":5,"area":null},{"id":"2210.06330","title":"CoRRECT: A Deep Unfolding Framework for Motion-Corrected Quantitative R2* Mapping","created":"2022-10-12","cited_by_count":5,"area":null},{"id":"2305.04047","title":"Degradation-Noise-Aware Deep Unfolding Transformer for Hyperspectral Image Denoising","created":"2023-05-06","cited_by_count":5,"area":null},{"id":"2412.11108","title":"Plug-and-Play Priors as a Score-Based Method","created":"2024-12-15","cited_by_count":5,"area":null},{"id":"2506.21460","title":"Wild refitting for black box prediction","created":"2025-06-26","cited_by_count":5,"area":null},{"id":"2207.08939","title":"Learning Sparsity-Promoting Regularizers using Bilevel Optimization","created":"2022-07-18","cited_by_count":4,"area":null},{"id":"2210.11113","title":"PAC-Bayesian Learning of Optimization Algorithms","created":"2022-10-20","cited_by_count":4,"area":null},{"id":"2310.05812","title":"Provably Convergent Data-Driven Convex-Nonconvex Regularization","created":"2023-10-09","cited_by_count":4,"area":null},{"id":"2311.08972","title":"Unsupervised approaches based on optimal transport and convex analysis for inverse problems in imaging","created":"2023-11-15","cited_by_count":4,"area":null},{"id":"2311.17744","title":"Variational Bayes image restoration with compressive autoencoders","created":"2023-11-29","cited_by_count":4,"area":null},{"id":"2505.08909","title":"Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Inverse Problems","created":"2025-05-13","cited_by_count":4,"area":null},{"id":"2202.02952","title":"Supervision by Denoising for Medical Image Segmentation","created":"2022-02-07","cited_by_count":3,"area":null},{"id":"2202.04961","title":"Monotonically Convergent Regularization by Denoising","created":"2022-02-10","cited_by_count":3,"area":null},{"id":"2205.03677","title":"Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms","created":"2022-05-07","cited_by_count":3,"area":null},{"id":"2302.05587","title":"Hierarchical Optimization-Derived Learning","created":"2023-02-11","cited_by_count":3,"area":null},{"id":"2311.13682","title":"Single-Shot Plug-and-Play Methods for Inverse Problems","created":"2023-11-22","cited_by_count":3,"area":null},{"id":"2311.18810","title":"Convergence of Nonconvex PnP-ADMM with MMSE Denoisers","created":"2023-11-30","cited_by_count":3,"area":null},{"id":"2401.00275","title":"An $\\ell^1$-Plug-and-Play Approach for MPI Using a Zero Shot Denoiser with Evaluation on the 3D Open MPI Dataset","created":"2023-12-30","cited_by_count":3,"area":null},{"id":"2401.08115","title":"No-Clean-Reference Image Super-Resolution: Application to Electron Microscopy","created":"2024-01-16","cited_by_count":3,"area":null},{"id":"2410.14994","title":"Quanta Video Restoration","created":"2024-10-19","cited_by_count":3,"area":null},{"id":"2501.13472","title":"Radio Map Estimation via Latent Domain Plug-and-Play Denoising","created":"2025-01-23","cited_by_count":3,"area":null},{"id":"2504.10929","title":"Cross-Frequency Implicit Neural Representation with Self-Evolving Parameters","created":"2025-04-15","cited_by_count":3,"area":null},{"id":"2603.12057","title":"Adaptive Weighted h-Transform Sampling for Coarse-Guided Visual Generation","created":"2026-03-12","cited_by_count":3,"area":null},{"id":"2110.04966","title":"Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework","created":"2021-10-11","cited_by_count":2,"area":null},{"id":"2207.12056","title":"REPNP: Plug-and-Play with Deep Reinforcement Learning Prior for Robust Image Restoration","created":"2022-07-25","cited_by_count":2,"area":null},{"id":"2210.10605","title":"Provably Convergent Plug & Play Linearized ADMM, applied to Deblurring Spatially Varying Kernels","created":"2022-10-19","cited_by_count":2,"area":null},{"id":"2302.02519","title":"RDFNet: Regional Dynamic FISTA-Net for Spectral Snapshot Compressive Imaging","created":"2023-02-06","cited_by_count":2,"area":null},{"id":"2310.02897","title":"How Much Training Data is Memorized in Overparameterized Autoencoders? An Inverse Problem Perspective on Memorization Evaluation","created":"2023-10-04","cited_by_count":2,"area":null}],"next_cursor":"100"}