{"list":"other","total":80,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"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":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"2207.12598","title":"Classifier-Free Diffusion Guidance","created":"2022-07-26","cited_by_count":5847},{"id":"2302.05543","title":"Adding Conditional Control to Text-to-Image Diffusion Models","created":"2023-02-10","cited_by_count":5503},{"id":"2403.03206","title":"Scaling Rectified Flow Transformers for High-Resolution Image Synthesis","created":"2024-03-05","cited_by_count":4181},{"id":"1907.05600","title":"Generative Modeling by Estimating Gradients of the Data Distribution","created":"2019-07-12","cited_by_count":4101},{"id":"1312.6114","title":"Auto-Encoding Variational Bayes","created":"2013-12-20","cited_by_count":4053},{"id":"2208.12242","title":"DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation","created":"2022-08-25","cited_by_count":3300},{"id":"2010.08895","title":"Fourier Neural Operator for Parametric Partial Differential Equations","created":"2020-10-18","cited_by_count":2908},{"id":"2311.15127","title":"Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets","created":"2023-11-25","cited_by_count":2581},{"id":"2104.07636","title":"Image Super-Resolution via Iterative Refinement","created":"2021-04-15","cited_by_count":1511},{"id":"2201.09865","title":"RePaint: Inpainting using Denoising Diffusion Probabilistic Models","created":"2022-01-24","cited_by_count":1430},{"id":"2104.13478","title":"Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges","created":"2021-04-27","cited_by_count":1167},{"id":"1602.07576","title":"Group Equivariant Convolutional Networks","created":"2016-02-24","cited_by_count":1165},{"id":"2006.09011","title":"Improved Techniques for Training Score-Based Generative Models","created":"2020-06-16","cited_by_count":1043},{"id":"2102.09844","title":"E(n) Equivariant Graph Neural Networks","created":"2021-02-19","cited_by_count":965},{"id":"2410.18072","title":"WorldSimBench: Towards Video Generation Models as World Simulators","created":"2024-10-23","cited_by_count":881},{"id":"1802.08219","title":"Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds","created":"2018-02-22","cited_by_count":746},{"id":"2203.17003","title":"Equivariant Diffusion for Molecule Generation in 3D","created":"2022-03-31","cited_by_count":677},{"id":"2106.05931","title":"Score-based Generative Modeling in Latent Space","created":"2021-06-10","cited_by_count":636},{"id":"2006.10503","title":"SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks","created":"2020-06-18","cited_by_count":607},{"id":"2111.08005","title":"Solving Inverse Problems in Medical Imaging with Score-Based Generative Models","created":"2021-11-15","cited_by_count":521},{"id":"2108.08481","title":"Neural Operator: Learning Maps Between Function Spaces","created":"2021-08-19","cited_by_count":414},{"id":"1704.03264","title":"Learning Deep CNN Denoiser Prior for Image Restoration","created":"2017-04-11","cited_by_count":408},{"id":"2305.16322","title":"Uni-ControlNet: All-in-One Control to Text-to-Image Diffusion Models","created":"2023-05-25","cited_by_count":359},{"id":"1703.03208","title":"Compressed Sensing using Generative Models","created":"2017-03-09","cited_by_count":339},{"id":"2303.13516","title":"Ablating Concepts in Text-to-Image Diffusion Models","created":"2023-03-23","cited_by_count":317},{"id":"2110.05243","title":"Score-based diffusion models for accelerated MRI","created":"2021-10-08","cited_by_count":311},{"id":"1611.02862","title":"The Little Engine that Could: Regularization by Denoising (RED)","created":"2016-11-09","cited_by_count":307},{"id":"2108.01368","title":"Robust Compressed Sensing MRI with Deep Generative Priors","created":"2021-08-03","cited_by_count":286},{"id":"2211.07804","title":"Diffusion Models for Medical Image Analysis: A Comprehensive Survey","created":"2022-11-14","cited_by_count":273},{"id":"2002.12880","title":"Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data","created":"2020-02-25","cited_by_count":248},{"id":"1411.5908","title":"Understanding image representations by measuring their equivariance and equivalence","created":"2014-11-21","cited_by_count":243},{"id":"2208.05314","title":"Convergence of denoising diffusion models under the manifold hypothesis","created":"2022-08-10","cited_by_count":242},{"id":"1805.12177","title":"Why do deep convolutional networks generalize so poorly to small image transformations?","created":"2018-05-30","cited_by_count":198},{"id":"2303.03543","title":"3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction","created":"2023-03-06","cited_by_count":177},{"id":"2311.16424","title":"Manifold Preserving Guided Diffusion","created":"2023-11-28","cited_by_count":157},{"id":"2309.04475","title":"Crystal Structure Prediction by Joint Equivariant Diffusion","created":"2023-07-30","cited_by_count":148},{"id":"2406.17763","title":"DiffusionPDE: Generative PDE-Solving Under Partial Observation","created":"2024-06-25","cited_by_count":108},{"id":"2201.11969","title":"Approximately Equivariant Networks for Imperfectly Symmetric Dynamics","created":"2022-01-28","cited_by_count":97},{"id":"2305.18453","title":"Conditional Diffusion Models for Semantic 3D Brain MRI Synthesis","created":"2023-05-29","cited_by_count":86},{"id":"2109.07103","title":"Automatic Symmetry Discovery with Lie Algebra Convolutional Network","created":"2021-09-15","cited_by_count":83},{"id":"1711.08014","title":"The Riemannian Geometry of Deep Generative Models","created":"2017-11-21","cited_by_count":82},{"id":"2007.02933","title":"Meta-Learning Symmetries by Reparameterization","created":"2020-07-06","cited_by_count":76},{"id":"2007.09969","title":"Fairwashing Explanations with Off-Manifold Detergent","created":"2020-07-20","cited_by_count":72},{"id":"1406.4175","title":"From Denoising to Compressed Sensing","created":"2014-06-16","cited_by_count":68},{"id":"2203.12621","title":"MR Image Denoising and Super-Resolution Using Regularized Reverse Diffusion","created":"2022-03-23","cited_by_count":67},{"id":"2407.01812","title":"Equivariant Diffusion Policy","created":"2024-07-01","cited_by_count":66},{"id":"1704.06625","title":"Learned D-AMP: Principled Neural Network based Compressive Image Recovery","created":"2017-04-21","cited_by_count":65},{"id":"2210.15228","title":"Solving Audio Inverse Problems with a Diffusion Model","created":"2022-10-27","cited_by_count":62},{"id":"2410.16415","title":"On conditional diffusion models for PDE simulations","created":"2024-10-21","cited_by_count":60},{"id":"2203.02194","title":"Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection","created":"2022-03-04","cited_by_count":59},{"id":"2104.00317","title":"Explore Image Deblurring via Blur Kernel Space","created":"2021-04-01","cited_by_count":58},{"id":"2110.10211","title":"Learning Partial Equivariances from Data","created":"2021-10-19","cited_by_count":45},{"id":"2401.11037","title":"Equivariant Graph Neural Operator for Modeling 3D Dynamics","created":"2024-01-19","cited_by_count":38},{"id":"2303.12410","title":"EDGI: Equivariant Diffusion for Planning with Embodied Agents","created":"2023-03-22","cited_by_count":36},{"id":"2209.01725","title":"Imaging with Equivariant Deep Learning","created":"2022-09-05","cited_by_count":35},{"id":"2404.04785","title":"Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution","created":"2024-04-07","cited_by_count":30},{"id":"2208.11665","title":"Statistical exploration of the Manifold Hypothesis","created":"2022-08-24","cited_by_count":29},{"id":"2203.12513","title":"Sensing Theorems for Unsupervised Learning in Linear Inverse Problems","created":"2022-03-23","cited_by_count":28},{"id":"2503.22600","title":"Generative Latent Neural PDE Solver using Flow Matching","created":"2025-03-28","cited_by_count":28},{"id":"2201.02331","title":"iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection","created":"2022-01-07","cited_by_count":27},{"id":"2312.01831","title":"Equivariant plug-and-play image reconstruction","created":"2023-12-04","cited_by_count":26},{"id":"2309.00783","title":"Diffusion Modeling with Domain-conditioned Prior Guidance for Accelerated MRI and qMRI Reconstruction","created":"2023-09-02","cited_by_count":22},{"id":"2403.11415","title":"DreamSampler: Unifying Diffusion Sampling and Score Distillation for Image Manipulation","created":"2024-03-18","cited_by_count":22},{"id":"2308.06564","title":"EquiDiff: A Conditional Equivariant Diffusion Model For Trajectory Prediction","created":"2023-08-12","cited_by_count":21},{"id":"2304.02637","title":"GenPhys: From Physical Processes to Generative Models","created":"2023-04-05","cited_by_count":19},{"id":"2206.07387","title":"The Manifold Hypothesis for Gradient-Based Explanations","created":"2022-06-15","cited_by_count":16},{"id":"2503.21985","title":"Improving Equivariant Networks with Probabilistic Symmetry Breaking","created":"2025-03-27","cited_by_count":16},{"id":"2304.02628","title":"What Affects Learned Equivariance in Deep Image Recognition Models?","created":"2023-04-05","cited_by_count":15},{"id":"2312.11232","title":"Scale-Equivariant Imaging: Self-Supervised Learning for Image Super-Resolution and Deblurring","created":"2023-12-18","cited_by_count":14},{"id":"2405.05852","title":"Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control","created":"2024-05-09","cited_by_count":11},{"id":"2411.04225","title":"Approximate Equivariance in Reinforcement Learning","created":"2024-11-06","cited_by_count":9}],"next_cursor":null}