anassinator/gp
Differentiable Gaussian Process implementation for PyTorch
This tool helps machine learning engineers and researchers build and evaluate models that predict outcomes based on data. You provide your training data's inputs and outputs, and it generates predictions along with an estimate of their uncertainty. This is for professionals working with deep learning frameworks like PyTorch who need robust probabilistic predictions.
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Use this if you are a machine learning practitioner working with PyTorch and need a flexible, differentiable Gaussian Process implementation for probabilistic regression or Bayesian optimization tasks.
Not ideal if you are not familiar with machine learning concepts or PyTorch, as this is a technical library for developers.
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22
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2
Language
Python
License
MIT
Category
Last pushed
Jul 08, 2018
Commits (30d)
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