TSFpaper
The repository provides a comprehensive collection of over 300 papers on time series and spatio-temporal forecasting, categorized by model type. It is regularly updated with the latest studies from leading conferences, journals, and arXiv, supporting various kinds of forecasting such as univariate, multivariate, and spatio-temporal. It explains complex concepts and how deep learning affects model flexibility, and explores emerging subjects like irregular time series and recent innovations like the Mamba model. Contributions of relevant papers are welcome to further enrich this forecasting research resource.
