LukasRinder/normalizing-flows
Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
This project offers tools to build advanced AI models that can accurately estimate the probability distribution of complex data or generate new, realistic data samples from scratch. You can input various datasets, like sensor readings, financial time series, or images, and output either a detailed understanding of the data's underlying patterns or entirely new data that mimics the original. This is ideal for machine learning researchers, data scientists, and AI developers working on generative models or anomaly detection.
148 stars. No commits in the last 6 months.
Use this if you need to understand the complex probability distribution of your data or generate new data samples that are statistically similar to your original dataset.
Not ideal if you are looking for out-of-the-box, plug-and-play solutions for common tasks like classification or regression without diving into the underlying generative modeling techniques.
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148
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36
Language
Jupyter Notebook
License
GPL-3.0
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Last pushed
Sep 29, 2025
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