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GitHub topics: partially-observed-time-series

WenjieDu/PyPOTS

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation, classification, clustering, forecasting, & anomaly detection on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values

Language: Python - Size: 2.29 MB - Last synced: 1 day ago - Pushed: 1 day ago - Stars: 745 - Forks: 72

WenjieDu/TSDB

Time Series Data Beans: a Python toolbox loads 169 public time-series datasets for machine learning/deep learning with a single line of code.

Language: Python - Size: 230 KB - Last synced: about 24 hours ago - Pushed: 1 day ago - Stars: 123 - Forks: 13

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

Language: Python - Size: 587 KB - Last synced: 11 days ago - Pushed: about 1 month ago - Stars: 271 - Forks: 47

Related Keywords
time-series 3 partially-observed-time-series 3 deep-learning 3 machine-learning 3 imputation 3 time-series-analysis 2 pytorch 2 missing-values 2 interpolation 2 forecasting 2 classification 2 irregular-sampling 1 partially-observed 1 partially-observed-data 1 incomplete-time-series 1 incomplete-data 1 self-attention 1 time-series-imputation 1 impute 1 transformer 1 imputation-model 1 attention-mechanism 1 attention 1 time-series-datasets 1 time-series-database 1 database 1 science-research 1 neural-network 1 missingness 1 industrial 1 incomplete 1 healthcare 1 data-science 1 data-mining 1 clustering 1