Enhancing deep reinforcement learning: A tutorial on generative diffusion models in network optimization

H Du, R Zhang, Y Liu, J Wang, Y Lin… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of
Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across …

Diffusion models for time-series applications: a survey

L Lin, Z Li, R Li, X Li, J Gao - Frontiers of Information Technology & …, 2024 - Springer
Diffusion models, a family of generative models based on deep learning, have become
increasingly prominent in cutting-edge machine learning research. With distinguished …

A survey on diffusion models for time series and spatio-temporal data

Y Yang, M **, H Wen, C Zhang, Y Liang, L Ma… - ar** review
B Zanchi, G Monachino, L Fiorillo, G Conte… - Computers in Biology …, 2025 - Elsevier
The scientific community has recently shown increasing interest in generating synthetic ECG
data. In particular, synthetic ECG signals can be beneficial for understanding cardiac …

Exploring a new frontier in cardiac diagnosis: ECG analysis enhanced by machine learning and parametric quartic spline modeling

A Mishra, S Bhusnur, SK Mishra, P Singh - Journal of Electrocardiology, 2024 - Elsevier
The heart's study holds paramount importance in human physiology, driving valuable
research in cardiovascular health. However, assessing Electrocardiogram (ECG) analysis …

FDF: Flexible Decoupled Framework for Time Series Forecasting with Conditional Denoising and Polynomial Modeling

J Zhang, M Cheng, X Tao, Z Liu, D Wang - arxiv preprint arxiv:2410.13253, 2024 - arxiv.org
Time series forecasting is vital in numerous web applications, influencing critical decision-
making across industries. While diffusion models have recently gained increasing popularity …