AaltoML/BayesNewton
Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.
This library helps machine learning practitioners build models that make predictions and quantify uncertainty using Gaussian processes. It takes in various types of data and outputs probabilistic predictions, useful for tasks like forecasting, classification, and understanding complex system behavior. Researchers and data scientists who need robust, explainable predictive models will find this useful.
242 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are developing or applying advanced machine learning models and need flexible, computationally efficient ways to perform approximate Bayesian inference with Gaussian processes.
Not ideal if you are looking for a simple, out-of-the-box machine learning solution without delving into advanced probabilistic modeling techniques.
Stars
242
Forks
32
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 22, 2023
Commits (30d)
0
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