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Wenjie Du

WenjieDu
where time series is observed & valued

I'm making my contributions to partially-observed time-series (POTS) modeling systems, benchmarks, and applications.

You can also sponsor me on:

Besides, you can sponsor me with cryptocurrencies, and here are my wallet addresses:

  • DOGE wallet address: D7nHiEpq1nsDQgpUHknvMGnQ9wRADRPyGQ
  • XMR wallet address: 85Hd35Cqg2TaW6sLA5eYBbMmC2iFDMfKtBTL6PMJMiPBXVDf5jFKr6wf1iEqzTcvhXETqWPDACTMNcHiXmQfVo8T5vU7vjk
  • ETH wallet address: 0x9ab544f3435fbfbc21d3ead0d25741e54372d19e
@WenjieDu

It's a great honor to see you are using my works! 😃 I'll be able to cover my coffee☕️ costs once I'm sponsored for $50 each month!

Current sponsors 1

@vinogradovkonst
Past sponsors 1
@demstalferez

Featured work

  1. 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 imputatio…

    Python 1,134
  2. 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-s…

    Python 338
  3. WenjieDu/TSDB

    a Python toolbox loads 172 public time series datasets for machine/deep learning with a single line of code. Datasets from multiple domains including healthcare, financial, power, traffic, weather,…

    Python 169
  4. WenjieDu/PyGrinder

    PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at…

    Python 37
  5. WenjieDu/BrewPOTS

    The tutorials for PyPOTS, guide you to model partially-observed time series datasets.

    Jupyter Notebook 59
  6. WenjieDu/Awesome_Imputation

    Awesome Deep Learning for Time-Series Imputation, including a must-read paper list about applying neural networks to impute incomplete time series containing NaN missing values/data

    Python 223

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