GitHub / 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

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/WenjieDu%2FSAITS

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

Funding links: https://github.com/sponsors/WenjieDu

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