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Variational inference is an increasingly popular method in statistics andmachine learning for approximating probability distributions. We developedLINFA (Library for Inference with Normalizing Flow and Annealing), a Pythonlibrary for variational inference to accommodate computationally expensivemodels and difficult-to-sample distributions with dependent parameters. Wediscuss the theoretical background, capabilities, and performance of LINFA invarious benchmarks. LINFA is publicly available on GitHub athttps://github.com/desResLab/LINFA.

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