hcllaw / VBAgg

Implements aggregate output learning with Gaussian processes

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VBAgg

Python code (tested on 2.7) for aggregate output learning with Gaussian processes, the details are described in the following paper:

H. Law, D. Sejdinovic, E. Cameron, T. CD Lucas, S. Flaxman, K. Battle, K. Fukumizu, Variational Learning on Aggregate Outputs with Gaussian Processes, NeurIPS 2018 (https://arxiv.org/abs/1805.08463)

Due to data confidentiality reasons, we do not provide the malaria data we used in the paper.

Setup

To setup as a package, clone the repository and run

python setup.py develop

This package also requires TensorFlow (tested on v1.7.0) to be installed.

Structure

The directory is organised as follows:

  • vb_agg_learn: contains the main code, including toy data scripts
  • experiment: contains the API code and experimental configuration code

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Implements aggregate output learning with Gaussian processes

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