{"list":"other","total":52,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255},{"id":"1503.03585","title":"Deep Unsupervised Learning using Nonequilibrium Thermodynamics","created":"2015-03-12","cited_by_count":7058},{"id":"2206.00364","title":"Elucidating the Design Space of Diffusion-Based Generative Models","created":"2022-06-01","cited_by_count":3045},{"id":"2303.04137","title":"Diffusion Policy: Visuomotor Policy Learning via Action Diffusion","created":"2023-03-07","cited_by_count":2838},{"id":"1603.06560","title":"Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization","created":"2016-03-21","cited_by_count":699},{"id":"2111.03794","title":"Physics-Informed Neural Operator for Learning Partial Differential Equations","created":"2021-11-06","cited_by_count":527},{"id":"2111.08005","title":"Solving Inverse Problems in Medical Imaging with Score-Based Generative Models","created":"2021-11-15","cited_by_count":521},{"id":"1811.08839","title":"fastMRI: An Open Dataset and Benchmarks for Accelerated MRI","created":"2018-11-21","cited_by_count":470},{"id":"2410.17725","title":"YOLOv11: An Overview of the Key Architectural Enhancements","created":"2024-10-23","cited_by_count":425},{"id":"1712.02862","title":"MoDL: Model Based Deep Learning Architecture for Inverse Problems","created":"2017-12-07","cited_by_count":387},{"id":"1704.00447","title":"Learning a Variational Network for Reconstruction of Accelerated MRI Data","created":"2017-04-03","cited_by_count":342},{"id":"2110.05243","title":"Score-based diffusion models for accelerated MRI","created":"2021-10-08","cited_by_count":311},{"id":"2108.01368","title":"Robust Compressed Sensing MRI with Deep Generative Priors","created":"2021-08-03","cited_by_count":286},{"id":"1711.05597","title":"Advances in Variational Inference","created":"2017-11-15","cited_by_count":236},{"id":"2206.04119","title":"Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem","created":"2022-06-08","cited_by_count":236},{"id":"1704.02422","title":"A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction","created":"2017-04-08","cited_by_count":232},{"id":"1704.08841","title":"Image reconstruction by domain transform manifold learning","created":"2017-04-28","cited_by_count":232},{"id":"2306.17775","title":"Practical and Asymptotically Exact Conditional Sampling in Diffusion Models","created":"2023-06-30","cited_by_count":232},{"id":"1709.02576","title":"Deep learning for undersampled MRI reconstruction","created":"2017-09-08","cited_by_count":91},{"id":"2010.03106","title":"Structured Logconcave Sampling with a Restricted Gaussian Oracle","created":"2020-10-07","cited_by_count":86},{"id":"1709.00753","title":"Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss","created":"2017-09-03","cited_by_count":82},{"id":"2202.06386","title":"Improved analysis for a proximal algorithm for sampling","created":"2022-02-13","cited_by_count":73},{"id":"1809.04693","title":"An Online Plug-and-Play Algorithm for Regularized Image Reconstruction","created":"2018-09-12","cited_by_count":70},{"id":"1905.01332","title":"A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization","created":"2019-05-03","cited_by_count":68},{"id":"1912.05854","title":"RARE: Image Reconstruction using Deep Priors Learned without Ground Truth","created":"2019-12-12","cited_by_count":64},{"id":"2010.14462","title":"Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging","created":"2020-10-27","cited_by_count":57},{"id":"2402.14285","title":"Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion","created":"2024-02-22","cited_by_count":54},{"id":"2310.10835","title":"Provable Probabilistic Imaging using Score-Based Generative Priors","created":"2023-10-16","cited_by_count":51},{"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},{"id":"1804.05809","title":"Split-and-augmented Gibbs sampler - Application to large-scale inference problems","created":"2018-04-16","cited_by_count":47},{"id":"2202.01479","title":"Bayesian MRI Reconstruction with Joint Uncertainty Estimation using Diffusion Models","created":"2022-02-03","cited_by_count":47},{"id":"2111.02926","title":"OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion","created":"2021-11-04","cited_by_count":44},{"id":"1711.11386","title":"MR image reconstruction using deep density priors","created":"2017-11-30","cited_by_count":37},{"id":"1808.03620","title":"Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks","created":"2018-08-10","cited_by_count":37},{"id":"1810.03990","title":"DeepNIS: Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering","created":"2018-10-04","cited_by_count":31},{"id":"1909.01127","title":"MRI Reconstruction Using Deep Bayesian Estimation","created":"2019-09-03","cited_by_count":29},{"id":"2109.03812","title":"fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data","created":"2021-09-08","cited_by_count":29},{"id":"2305.04120","title":"A Latent Diffusion Model for Protein Structure Generation","created":"2023-05-06","cited_by_count":28},{"id":"1806.04139","title":"Deep speckle correlation: a deep learning approach towards scalable imaging through scattering media","created":"2018-06-11","cited_by_count":23},{"id":"2101.09379","title":"SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees","created":"2021-01-22","cited_by_count":18},{"id":"1911.13241","title":"SIMBA: Scalable Inversion in Optical Tomography using Deep Denoising Priors","created":"2019-11-29","cited_by_count":16},{"id":"1912.05330","title":"Diffraction tomography with a deep image prior","created":"2019-12-10","cited_by_count":15},{"id":"1503.02945","title":"Fast Multi-class Dictionaries Learning with Geometrical Directions in MRI Reconstruction","created":"2015-03-10","cited_by_count":10},{"id":"1803.06594","title":"Efficient and accurate inversion of multiple scattering with deep learning","created":"2018-03-18","cited_by_count":10},{"id":"2406.02785","title":"Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors","created":"2024-06-04","cited_by_count":7},{"id":"1302.2712","title":"Bayesian Nonparametric Dictionary Learning for Compressed Sensing MRI","created":"2013-02-12","cited_by_count":5},{"id":"1705.04281","title":"SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering","created":"2017-05-05","cited_by_count":5},{"id":"1708.01663","title":"Accelerated Image Reconstruction for Nonlinear Diffractive Imaging","created":"2017-08-04","cited_by_count":3},{"id":"2311.18012","title":"Bayesian Imaging for Radio Interferometry with Score-Based Priors","created":"2023-11-29","cited_by_count":3}],"next_cursor":null}