search

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
https://doi.org/10.1016/j.eswa.2023.119619
MIT License
292 stars 48 forks source link

why do not have the code for ETTDataset #24

Closed NewKeyTo closed 1 year ago

WenjieDu commented 1 year ago

Hi there,

Thank you so much for your attention to SAITS! If you find SAITS is helpful to your work, please star⭐️ this repository. Your star is your recognition, which can let others notice SAITS. It matters and is definitely a kind of contribution.

I have received your message and will respond ASAP. Thank you again for your patience! 😃

Best,
Wenjie

WenjieDu commented 1 year ago

Hi,

The experiments conducted on ETT dataset are added lately and additionally to make the reviewer satisfied with the number of datasets used in this work. If you refer to an earlier version of SAITS paper, you will see that ETT doesn't exist.

Will clean the related scripts and add them to this repo. If it doesn't bother you, please star 🌟 this repo to help more people notice this useful work. Thanks.

NewKeyTo commented 1 year ago

ok, thank you for your work and reply!

WenjieDu commented 1 year ago

Updated. Check out PR #25. Please pay a visit to the toolbox PyPOTS https://github.com/WenjieDu/PyPOTS if you're interested in modeling partially-observed time series (POTS). It deserves your attention ;-) Please star 🌟 PyPOTS if you like it.