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- W4221159595 abstract "py-irt is a Python library for fitting Bayesian Item Response Theory (IRT) models. py-irt estimates latent traits of subjects and items, making it appropriate for use in IRT tasks as well as ideal-point models. py-irt is built on top of the Pyro and PyTorch frameworks and uses GPU-accelerated training to scale to large data sets. Code, documentation, and examples can be found at https://github.com/nd-ball/py-irt. py-irt can be installed from the GitHub page or the Python Package Index (PyPI)." @default.
- W4221159595 created "2022-04-03" @default.
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- W4221159595 date "2022-03-02" @default.
- W4221159595 modified "2023-09-24" @default.
- W4221159595 title "py-irt: A Scalable Item Response Theory Library for Python" @default.
- W4221159595 doi "https://doi.org/10.48550/arxiv.2203.01282" @default.
- W4221159595 hasPublicationYear "2022" @default.
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