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Deriving Variational Inference and Expectation Maximization Algorithms From Scratch

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Bayesian-Machine-Learning

Deriving expectation maximization and variational inference algorithms from scratch.

Also check out my article: https://medium.com

"Variational Bayesian Inference for Unsupervised Clustering"

  • Solved and released the first publicly available full mathematical derivation of a binomial mixture model given beta and Dirichlet priors using variational inference, including the exact evidence lower bound (ELBO)
  • Implemented in PyTorch to speed matrix multiplication in fast, closed-form parameter update equations versus automatic differentiation and MCMC methods common in popular packages like PyMC and BayesPy

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Deriving Variational Inference and Expectation Maximization Algorithms From Scratch

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