WenjieDu / SAITS

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

Date Created 2021-12-07 (3 years ago)

Commits 84 (last one 4 months ago)

Stargazers 350 (1 this week)

Watchers 6 (0 this week)

Forks 54

License mit

Ranking

RepositoryStats indexes 598,732 repositories, of these WenjieDu/SAITS is ranked #120,163 (80th percentile) for total stargazers, and #301,445 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #20,458/120,199.

WenjieDu/SAITS is also tagged with popular topics, for these it's ranked: deep-learning (#2,593/8543), machine-learning (#2,506/8091), pytorch (#1,753/6032), transformer (#281/1019), time-series (#199/674)

Other Information

Homepage URL: https://doi.org/10.1016/j.eswa.2023.119619

All Topics

impute pytorch attention imputation time-series transformer deep-learning interpolation missing-values self-attention incomplete-data imputation-model machine-learning irregular-sampling partially-observed attention-mechanism incomplete-time-series time-series-imputation partially-observed-data partially-observed-time-series

Star History

Github stargazers over time

Watcher History

Github watchers over time, collection started in '23

Recent Commit History

83 commits on the default branch (main) since jan '22

Yearly Commits

Commits to the default branch (main) per year

Issue History

Languages

The primary language is Python but there's also others...

Opengraph Image

updated: 2024-12-29 @ 05:28am, id: 435921975 / R_kgDOGfukNw