1. RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
    Gabriel Bénédict, Olivier Jeunen, Samuele Papa, Samarth Bhargav, Daan Odijk, Maarten de Rijke
    arXiv 2023. Paper  
    2023-06-15
    2023-06-15
  2. Data Augmentation for Seizure Prediction with Generative Diffusion Model
    Kai Shu, Yuchang Zhao, Le Wu, Aiping Liu, Ruobing Qian, Xun Chen
    arXiv 2023. Paper  
    2023-06-14
    2023-06-14
  3. Non-autoregressive Conditional Diffusion Models for Time Series Prediction
    Lifeng Shen, James Kwok
    arXiv 2023. Paper  
    2023-06-08
    2023-06-08
  4. DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
    Salva Rühling Cachay, Bo Zhao, Hailey James, Rose Yu
    arXiv 2023. Paper  
    2023-06-03
    2023-06-03
  5. DiffECG: A Generalized Probabilistic Diffusion Model for ECG Signals Synthesis
    Nour Neifar, Achraf Ben-Hamadou, Afef Mdhaffar, Mohamed Jmaiel
    arXiv 2023. Paper  
    2023-06-02
    2023-06-02
  6. DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model
    Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yi Wang
    arXiv 2023. Paper  
    2023-05-31
    2023-05-31
  7. Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition
    Si Zuo, Vitor Fortes Rey, Sungho Suh, Stephan Sigg, Paul Lukowicz
    arXiv 2023. Paper  
    2023-05-30
    2023-05-30
  8. Domain-Specific Denoising Diffusion Probabilistic Models for Brain Dynamics
    Yiqun Duan, Jinzhao Zhou, Zhen Wang, Yu-Cheng Chang, Yu-Kai Wang, Chin-Teng Lin
    arXiv 2023. Paper  
    2023-05-07
    2023-05-07
  9. CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis
    Chaejeong Lee, Jayoung Kim, Noseong Park
    ICML 2023. Paper  
    2023-04-25
    2023-04-25
  10. Customized Load Profiles Synthesis for Electricity Customers Based on Conditional Diffusion Models
    Zhenyi Wang, Hongcai Zhang
    arXiv 2023. Paper  
    2023-04-24
    2023-04-24
  11. Conditional Denoising Diffusion for Sequential Recommendation
    Yu Wang, Zhiwei Liu, Liangwei Yang, Philip S. Yu
    arXiv 2023. Paper  
    2023-04-22
    2023-04-22
  12. Diffusion Recommender Model
    Wenjie Wang, Yiyan Xu, Fuli Feng, Xinyu Lin, Xiangnan He, Tat-Seng Chua
    SIGIR 2023. Paper  
    2023-04-11
    2023-04-11
  13. Sequential Recommendation with Diffusion Models
    Hanwen Du, Huanhuan Yuan, Zhen Huang, Pengpeng Zhao, Xiaofang Zhou
    arXiv 2023. Paper  
    2023-04-10
    2023-04-10
  14. DiffuRec: A Diffusion Model for Sequential Recommendation
    Zihao Li, Aixin Sun, Chenliang Li
    arXiv 2023. Paper  
    2023-04-03
    2023-04-03
  15. Synthetic Health-related Longitudinal Data with Mixed-type Variables Generated using Diffusion Models
    Nicholas I-Hsien Kuo, Louisa Jorm, Sebastiano Barbieri
    arXiv 2023. Paper  
    2023-03-22
    2023-03-22
  16. EHRDiff: Exploring Realistic EHR Synthesis with Diffusion Models
    Hongyi Yuan, Songchi Zhou, Sheng Yu
    arXiv 2023. Paper   Github  
    2023-03-10
    2023-03-10
  17. Diffusing Gaussian Mixtures for Generating Categorical Data
    Florence Regol, Mark Coates
    arXiv 2023. Paper  
    2023-03-08
    2023-03-08
  18. EEG Synthetic Data Generation Using Probabilistic Diffusion Models
    Giulio Tosato, Cesare M. Dalbagno, Francesco Fumagalli
    Synapsium 2023. Paper  
    2023-03-06
    2023-03-06
  19. Synthesizing Mixed-type Electronic Health Records using Diffusion Models
    Taha Ceritli, Ghadeer O. Ghosheh, Vinod Kumar Chauhan, Tingting Zhu, Andrew P. Creagh, David A. Clifton
    arXiv 2023. Paper  
    2023-02-28
    2023-02-28
  20. PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation
    Mingzhe Liu, Han Huang, Hao Feng, Leilei Sun, Bowen Du, Yanjie Fu
    ICDE 2023. Paper   Github  
    2023-02-20
    2023-02-20
  21. MedDiff: Generating Electronic Health Records using Accelerated Denoising Diffusion Model
    Huan He, Shifan Zhao, Yuanzhe Xi, Joyce C Ho
    arXiv 2023. Paper  
    2023-02-08
    2023-02-08
  22. Diffusion-based Conditional ECG Generation with Structured State Space Models
    Juan Miguel Lopez Alcaraz, Nils Strodthoff
    arXiv 2023. Paper  
    2023-01-19
    2023-01-19
  23. TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting
    Ping Chang, Huayu Li, Stuart F. Quan, Janet Roveda, Ao Li
    arXiv 2023. Paper   Github  
    2023-01-16
    2023-01-16
  24. Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement
    Yan Li, Xinjiang Lu, Yaqing Wang, Dejing Dou
    NeurIPS 2022. Paper   Github  
    2023-01-08
    2023-01-08
  25. Denoising diffusion probabilistic models for probabilistic energy forecasting
    Esteban Hernandez, Jonathan Dumas
    Powertech 2022. Paper  
    2022-12-06
    2022-12-06
  26. Modeling Temporal Data as Continuous Functions with Process Diffusion
    Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
    arXiv 2022. Paper  
    2022-11-04
    2022-11-04
  27. Modeling Temporal Data as Continuous Functions with Process Diffusion
    Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
    arXiv 2022. Paper  
    2022-11-04
    2022-11-04
  28. Diffusion models for missing value imputation in tabular data
    Shuhan Zheng, Nontawat Charoenphakdee
    NeurIPS 2022. Paper  
    2022-10-31
    2022-10-31
  29. TabDDPM: Modelling Tabular Data with Diffusion Models
    Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev, Artem Babenko
    arXiv 2022. Paper   Github  
    2022-09-30
    2022-09-30
  30. Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
    Juan Miguel Lopez Alcaraz, Nils Strodthoff
    TMLR 2022. Paper   Github  
    2022-08-19
    2022-08-19
  31. Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
    Juan Miguel Lopez Alcaraz, Nils Strodthoff
    TMLR 2022. Paper   Github  
    2022-08-19
    2022-08-19
  32. DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal
    Huayu Li, Gregory Ditzler, Janet Roveda, Ao Li
    IEEE JBHI 2023. Paper  
    2022-07-31
    2022-07-31
  33. Recommendation via Collaborative Diffusion Generative Model
    Joojo Walker, Ting Zhong, Fengli Zhang, Qiang Gao, Fan Zhou
    KSEM 2022. Paper  
    2022-07-19
    2022-07-19
  34. CARD: Classification and Regression Diffusion Models
    Xizewen Han, Huangjie Zheng, Mingyuan Zhou
    NeurIPS 2022. Paper  
    2022-06-15
    2022-06-15
  35. Neural Markov Controlled SDE: Stochastic Optimization for Continuous-Time Data
    Sung Woo Park, Kyungjae Lee, Junseok Kwon
    ICLR 2022. Paper  
    2021-09-29
    2021-09-29
  36. CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
    Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon
    NeurIPS 2021. Paper   Github  
    2021-07-07
    2021-07-07
  37. ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models
    Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
    arXiv 2021. Paper   Github  
    2021-06-18
    2021-06-18
  38. Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
    Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
    ICLR 2021. Paper   Github  
    2021-02-02
    2021-02-02
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