A Survey on Diffusion Models for Time Series and Spatio-Temporal Data

arXiv:2404.18886v1 Announce Type: new
Abstract: The study of time series data is crucial for understanding trends and anomalies over time, enabling predictive insights across various sectors. Spatio-temporal data, on the other hand, is vital for analyzing phenomena in both space and time, providing a dynamic perspective on complex system interactions. Recently, diffusion models have seen widespread application in time series and spatio-temporal data mining. Not only do they enhance the generative and inferential capabilities for sequential and temporal data, but …

abstract arxiv cs.ai cs.lg data diffusion diffusion models dynamic enabling insights perspective predictive predictive insights series space space and time study survey temporal time series trends type understanding vital