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Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression

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Approximate Inference and Learning in Probabilistic Models

Assignment for Approximate Inference and Learning in Probabilistic Models (COMP0085) at UCL 2022

  • Variational Bayes & Automatic Relevance Determination (ARD)
  • Mean Field Learning
  • Loopy Belief Propagation
  • Gaussian Process Regression

To set up your python environment:

  1. Install poetry
pip install poetry
  1. Install dependencies
poetry install

Variational Bayes Automatic Relevance Determination:

Automatic Relevance Determination (8 Actual Latent Factors)

Mean Field Learning:

Learned Latent Factors

EM Free Energy

Loopy Belief Propagation:

Learned Latent Factors

EM Free Energy (doesn't converge)

Gaussian Process Regression:

CO2 Extrapolation

Kernel Hyper-Parameter Visualisation