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LINFA: a Python library for variational inference with normalizing flow and annealing

10 July 2023
Yu Wang
Emma R. Cobian
Jubilee Lee
Fang Liu
J. Hauenstein
Daniele E. Schiavazzi
    BDL
    AI4CE
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Abstract

Variational inference is an increasingly popular method in statistics and machine learning for approximating probability distributions. We developed LINFA (Library for Inference with Normalizing Flow and Annealing), a Python library for variational inference to accommodate computationally expensive models and difficult-to-sample distributions with dependent parameters. We discuss the theoretical background, capabilities, and performance of LINFA in various benchmarks. LINFA is publicly available on GitHub at https://github.com/desResLab/LINFA.

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