SAITS
by WenjieDu (personal account)
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… (description from the project’s GitHub page)
Repository facts
- Stars
- 513
- Forks
- 71
- Open issues and pull requests
- 0
- Primary language
- Python
- License
- MIT License (MIT)
- Owner
- WenjieDu · Personal account
- Created
- Dec 7, 2021
- Last push
- Aug 25, 2026
Topics
- attention
- attention-mechanism
- deep-learning
- imputation
- imputation-model
- impute
- incomplete-data
- incomplete-time-series
- interpolation
- irregular-sampling
- machine-learning
- missing-values
- partially-observed
- partially-observed-data
- partially-observed-time-series
- pytorch
- self-attention
- time-series
- time-series-imputation
- transformer
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