{"total":270,"rows":[{"id":"2107.03006","title":"Structured Denoising Diffusion Models in Discrete State-Spaces","created":"2021-07-07","cited_by_count":1719,"area":"wm"},{"id":"2209.00796","title":"Diffusion Models: A Comprehensive Survey of Methods and Applications","created":"2022-09-02","cited_by_count":1114,"area":"diffusion"},{"id":"2106.05931","title":"Score-based Generative Modeling in Latent Space","created":"2021-06-10","cited_by_count":636,"area":"diffusion"},{"id":"2106.01357","title":"Diffusion Schr\\\"odinger Bridge with Applications to Score-Based Generative Modeling","created":"2021-06-01","cited_by_count":602,"area":"diffusion"},{"id":"2107.03502","title":"CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation","created":"2021-07-07","cited_by_count":582,"area":"diffusion"},{"id":"2209.14734","title":"DiGress: Discrete Denoising diffusion for graph generation","created":"2022-09-29","cited_by_count":520,"area":"diffusion"},{"id":"2105.06337","title":"Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speech","created":"2021-05-13","cited_by_count":447,"area":"diffusion"},{"id":"2307.12348","title":"ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting","created":"2023-07-23","cited_by_count":365,"area":"diffusion"},{"id":"2101.12072","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","created":"2021-01-28","cited_by_count":337,"area":"diffusion"},{"id":"2110.05243","title":"Score-based diffusion models for accelerated MRI","created":"2021-10-08","cited_by_count":311,"area":"diffusion"},{"id":"2202.02514","title":"Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations","created":"2022-02-05","cited_by_count":283,"area":"diffusion"},{"id":"2302.04304","title":"Q-Diffusion: Quantizing Diffusion Models","created":"2023-02-08","cited_by_count":273,"area":"diffusion"},{"id":"2211.15736","title":"Post-training Quantization on Diffusion Models","created":"2022-11-28","cited_by_count":267,"area":"diffusion"},{"id":"2209.02646","title":"A Survey on Generative Diffusion Model","created":"2022-09-06","cited_by_count":240,"area":"diffusion"},{"id":"2302.08224","title":"DIFUSCO: Graph-based Diffusion Solvers for Combinatorial Optimization","created":"2023-02-16","cited_by_count":221,"area":"diffusion"},{"id":"2105.14080","title":"Gotta Go Fast When Generating Data with Score-Based Models","created":"2021-05-28","cited_by_count":219,"area":"diffusion"},{"id":"2211.00802","title":"Concrete Score Matching: Generalized Score Matching for Discrete Data","created":"2022-11-02","cited_by_count":148,"area":null},{"id":"2206.07696","title":"Diffusion Models for Video Prediction and Infilling","created":"2022-06-15","cited_by_count":135,"area":"diffusion"},{"id":"2210.05475","title":"GENIE: Higher-Order Denoising Diffusion Solvers","created":"2022-10-11","cited_by_count":127,"area":"diffusion"},{"id":"2205.13209","title":"Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization","created":"2022-05-26","cited_by_count":119,"area":null},{"id":"2402.04717","title":"InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior","created":"2024-02-07","cited_by_count":117,"area":null},{"id":"2204.01613","title":"SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators","created":"2022-04-04","cited_by_count":99,"area":null},{"id":"2212.06512","title":"DifFace: Blind Face Restoration with Diffused Error Contraction","created":"2022-12-13","cited_by_count":97,"area":"diffusion"},{"id":"2106.06819","title":"D2C: Diffusion-Denoising Models for Few-shot Conditional Generation","created":"2021-06-12","cited_by_count":96,"area":null},{"id":"2206.07632","title":"Exploring Chemical Space with Score-based Out-of-distribution Generation","created":"2022-06-06","cited_by_count":95,"area":null},{"id":"2403.14404","title":"Physics-Informed Diffusion Models","created":"2024-03-21","cited_by_count":90,"area":"diffusion"},{"id":"2102.00546","title":"GraphEBM: Molecular Graph Generation with Energy-Based Models","created":"2021-01-31","cited_by_count":85,"area":null},{"id":"2303.11717","title":"A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?","created":"2023-03-21","cited_by_count":84,"area":null},{"id":"2307.08849","title":"Autoregressive Diffusion Model for Graph Generation","created":"2023-07-17","cited_by_count":83,"area":"diffusion"},{"id":"2406.04843","title":"Variational Flow Matching for Graph Generation","created":"2024-06-07","cited_by_count":83,"area":"diffusion"},{"id":"2303.11579","title":"Diffusion-Based 3D Human Pose Estimation with Multi-Hypothesis Aggregation","created":"2023-03-21","cited_by_count":82,"area":null},{"id":"2301.13629","title":"DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models","created":"2023-01-31","cited_by_count":81,"area":"diffusion"},{"id":"2302.02591","title":"Generative Diffusion Models on Graphs: Methods and Applications","created":"2023-02-06","cited_by_count":81,"area":"diffusion"},{"id":"2305.04111","title":"Efficient and Degree-Guided Graph Generation via Discrete Diffusion Modeling","created":"2023-05-06","cited_by_count":80,"area":"diffusion"},{"id":"2405.11416","title":"Discrete-state Continuous-time Diffusion for Graph Generation","created":"2024-05-19","cited_by_count":76,"area":"diffusion"},{"id":"2210.01549","title":"Diffusion Models for Graphs Benefit From Discrete State Spaces","created":"2022-10-04","cited_by_count":73,"area":"diffusion"},{"id":"2202.00512","title":"Progressive Distillation for Fast Sampling of Diffusion Models","created":"2022-02-01","cited_by_count":69,"area":"diffusion"},{"id":"2203.06714","title":"A Survey on Deep Graph Generation: Methods and Applications","created":"2022-03-13","cited_by_count":69,"area":null},{"id":"2203.03623","title":"Measurement-conditioned Denoising Diffusion Probabilistic Model for Under-sampled Medical Image Reconstruction","created":"2022-03-05","cited_by_count":65,"area":"diffusion"},{"id":"2305.07508","title":"MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation","created":"2023-05-11","cited_by_count":65,"area":null},{"id":"2309.09968","title":"Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees","created":"2023-09-18","cited_by_count":62,"area":null},{"id":"2105.14257","title":"Diffusion-Based Representation Learning","created":"2021-05-29","cited_by_count":57,"area":null},{"id":"2308.05384","title":"Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization","created":"2023-08-10","cited_by_count":56,"area":"diffusion"},{"id":"2302.03596","title":"Graph Generation with Diffusion Mixture","created":"2023-02-07","cited_by_count":55,"area":null},{"id":"2311.09235","title":"Scalable Diffusion for Materials Generation","created":"2023-10-18","cited_by_count":54,"area":null},{"id":"2410.03601","title":"How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework","created":"2024-10-04","cited_by_count":48,"area":"diffusion"},{"id":"2502.00234","title":"Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms","created":"2025-02-01","cited_by_count":47,"area":"diffusion"},{"id":"2301.00427","title":"Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation","created":"2023-01-01","cited_by_count":46,"area":null},{"id":"2401.13858","title":"Graph Diffusion Transformers for Multi-Conditional Molecular Generation","created":"2024-01-24","cited_by_count":45,"area":"diffusion"},{"id":"2402.08095","title":"Convergence Analysis of Discrete Diffusion Model: Exact Implementation through Uniformization","created":"2024-02-12","cited_by_count":44,"area":"diffusion"},{"id":"2201.11972","title":"DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs","created":"2022-01-28","cited_by_count":43,"area":"diffusion"},{"id":"2212.01842","title":"GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation","created":"2022-12-04","cited_by_count":43,"area":null},{"id":"2410.19538","title":"Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series","created":"2024-10-25","cited_by_count":43,"area":"diffusion"},{"id":"2106.01098","title":"Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions","created":"2021-06-02","cited_by_count":39,"area":null},{"id":"2211.08892","title":"Fast Graph Generation via Spectral Diffusion","created":"2022-11-16","cited_by_count":36,"area":"diffusion"},{"id":"2312.11529","title":"Efficient and Scalable Graph Generation through Iterative Local Expansion","created":"2023-12-14","cited_by_count":36,"area":null},{"id":"2304.01565","title":"A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material","created":"2023-04-04","cited_by_count":35,"area":"diffusion"},{"id":"2406.06449","title":"Cometh: A continuous-time discrete-state graph diffusion model","created":"2024-06-10","cited_by_count":32,"area":"diffusion"},{"id":"2310.00800","title":"GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation","created":"2023-10-01","cited_by_count":31,"area":null},{"id":"2307.01646","title":"SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation","created":"2023-07-04","cited_by_count":28,"area":"diffusion"},{"id":"2305.12347","title":"Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation","created":"2023-05-21","cited_by_count":27,"area":"diffusion"},{"id":"2311.02142","title":"Sparse Training of Discrete Diffusion Models for Graph Generation","created":"2023-11-03","cited_by_count":27,"area":"diffusion"},{"id":"2305.16315","title":"NAP: Neural 3D Articulation Prior","created":"2023-05-25","cited_by_count":25,"area":null},{"id":"2402.02518","title":"Unifying Generation and Prediction on Graphs with Latent Graph Diffusion","created":"2024-02-04","cited_by_count":25,"area":"diffusion"},{"id":"2402.03687","title":"Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation","created":"2024-02-06","cited_by_count":25,"area":"diffusion"},{"id":"2104.09856","title":"Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning","created":"2021-04-20","cited_by_count":23,"area":null},{"id":"2401.04585","title":"EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models","created":"2024-01-09","cited_by_count":23,"area":"diffusion"},{"id":"2404.15625","title":"Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models","created":"2024-04-24","cited_by_count":22,"area":"diffusion"},{"id":"2209.05582","title":"Graph Neural Networks for Molecules","created":"2022-09-12","cited_by_count":21,"area":null},{"id":"2301.12906","title":"Curvature Filtrations for Graph Generative Model Evaluation","created":"2023-01-30","cited_by_count":19,"area":null},{"id":"2303.10108","title":"Data-Centric Learning from Unlabeled Graphs with Diffusion Model","created":"2023-03-17","cited_by_count":19,"area":"diffusion"},{"id":"2406.17341","title":"Generative Modelling of Structurally Constrained Graphs","created":"2024-06-25","cited_by_count":19,"area":"diffusion"},{"id":"2209.01170","title":"First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data","created":"2022-09-02","cited_by_count":18,"area":"diffusion"},{"id":"2211.10794","title":"NVDiff: Graph Generation through the Diffusion of Node Vectors","created":"2022-11-19","cited_by_count":18,"area":"diffusion"},{"id":"2310.13833","title":"GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?","created":"2023-10-20","cited_by_count":18,"area":"diffusion"},{"id":"2501.01073","title":"Graph Generative Pre-trained Transformer","created":"2025-01-02","cited_by_count":17,"area":null},{"id":"2301.10857","title":"Improving Graph Generation by Restricting Graph Bandwidth","created":"2023-01-25","cited_by_count":16,"area":null},{"id":"2305.16943","title":"DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models","created":"2023-05-26","cited_by_count":16,"area":"diffusion"},{"id":"2312.02230","title":"A Simple and Scalable Representation for Graph Generation","created":"2023-12-04","cited_by_count":16,"area":null},{"id":"2310.17153","title":"Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration","created":"2023-10-26","cited_by_count":14,"area":"diffusion"},{"id":"2503.23167","title":"Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks","created":"2025-03-29","cited_by_count":14,"area":null},{"id":"2402.16302","title":"Graph Diffusion Policy Optimization","created":"2024-02-26","cited_by_count":13,"area":"diffusion"},{"id":"2406.09357","title":"Advancing Graph Generation through Beta Diffusion","created":"2024-06-13","cited_by_count":13,"area":"diffusion"},{"id":"2502.02216","title":"Flatten Graphs as Sequences: Transformers are Scalable Graph Generators","created":"2025-02-04","cited_by_count":13,"area":null},{"id":"2208.07181","title":"One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstruction","created":"2022-08-15","cited_by_count":12,"area":null},{"id":"2401.02683","title":"Geometric-Facilitated Denoising Diffusion Model for 3D Molecule Generation","created":"2024-01-05","cited_by_count":12,"area":"diffusion"},{"id":"2404.03159","title":"HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud","created":"2024-04-04","cited_by_count":12,"area":"diffusion"},{"id":"2406.03686","title":"BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning","created":"2024-06-06","cited_by_count":12,"area":"deeprl"},{"id":"2210.13774","title":"From Points to Functions: Infinite-dimensional Representations in Diffusion Models","created":"2022-10-25","cited_by_count":11,"area":"diffusion"},{"id":"2309.16421","title":"Distilling ODE Solvers of Diffusion Models into Smaller Steps","created":"2023-09-28","cited_by_count":11,"area":"diffusion"},{"id":"2404.05662","title":"BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models","created":"2024-04-08","cited_by_count":11,"area":"diffusion"},{"id":"2410.09824","title":"LLM-Based Multi-Agent Systems are Scalable Graph Generative Models","created":"2024-10-13","cited_by_count":11,"area":"agents"},{"id":"2412.05926","title":"BiDM: Pushing the Limit of Quantization for Diffusion Models","created":"2024-12-08","cited_by_count":11,"area":"diffusion"},{"id":"2501.05673","title":"Network Diffuser for Placing-Scheduling Service Function Chains with Inverse Demonstration","created":"2025-01-10","cited_by_count":11,"area":null},{"id":"2503.13957","title":"DIFFVSGG: Diffusion-Driven Online Video Scene Graph Generation","created":"2025-03-18","cited_by_count":11,"area":null},{"id":"2107.01952","title":"Partition and Code: learning how to compress graphs","created":"2021-07-05","cited_by_count":10,"area":null},{"id":"2203.04698","title":"Score-Based Generative Models for Molecule Generation","created":"2022-03-07","cited_by_count":10,"area":"diffusion"},{"id":"2209.12064","title":"Face Super-Resolution Using Stochastic Differential Equations","created":"2022-09-24","cited_by_count":10,"area":"diffusion"},{"id":"2402.02464","title":"A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer","created":"2024-02-04","cited_by_count":10,"area":null},{"id":"2306.04873","title":"Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model","created":"2023-06-08","cited_by_count":9,"area":"diffusion"}],"next_cursor":"100"}