JonathanWenger/itergp
IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)
This is a specialized tool for machine learning researchers and practitioners who work with Gaussian Processes (GPs). It helps improve the accuracy and efficiency of GP models by accounting for computational uncertainties. You would use this by inputting your existing GP models, and it helps refine the posterior distribution and the overall computational process.
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Use this if you are a machine learning researcher or data scientist working with Gaussian Processes and need to enhance the precision and reliability of your model inference, especially when computational resources are a concern.
Not ideal if you are new to Gaussian Processes or are looking for a general-purpose machine learning library.
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Language
Python
License
MIT
Category
Last pushed
Apr 12, 2023
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