https://github.com/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
classification clustering data-mining data-science deep-learning forecasting healthcare imputation incomplete industrial interpolation machine-learning missing-values missingness neural-network partially-observed-time-series pytorch science-research time-series time-series-analysis
Added: over 1 year ago - Last Synced: 11 months ago - Created: March 29, 2022

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  • Main Language: Python
  • Commits: 793
  • Committers: 8
  • Issues: 144
  • Pull Requests: 267
  • Owner: WenjieDu
  • Stars: 750
  • Forks: 72
  • Packages: 1
  • Downloads: 34,267