WAX-ML: A Python library for machine learning and feedback loops on streaming data
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Abstract (arXiv)
Wax is what you put on a surfboard to avoid slipping. It is an essential tool to go surfing... We introduce WAX-ML a research-oriented Python library providing tools to design powerful machine learning algorithms and feedback loops working on streaming data. It strives to complement JAX with tools dedicated to time series. WAX-ML makes JAX-based programs easy to use for end-users working with pandas and xarray for data manipulation. It provides a simple mechanism for implementing feedback loops, allows the implementation of online learning and reinforcement learning algorithms with functions, and makes them easy to integrate by end-users working with the object-oriented reinforcement learning framework from the Gym library. It is released with an Apache open-source license on GitHub at https://github.com/eserie/wax-ml.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 46 references that are in the map. First posted on arXiv 11 Jun 2021.
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References · 9
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