sergioalvarezb / machine.learning.models.pytorch

Machine Learning models in general in PyTorch.

Machine Learning

Some cool machine learning stuff. Provide code, explanations or whatever I might find interesting.

Author: Juan Maroñas Molano ([email protected]) [PRHLT Research Center, Universidad Politécnica de Valencia]

Install

• Python version 3.7
• Requirements: pip install -r requirements.txt
• Might find useful to run ./install.sh

Models Implemented

In folder models you can find different models, follow instructions there:

• models/Bayesian_NN/

  • Mean Field Gaussian Variational BNN with pathwise gradient computations ref

  • Mean Field Gaussian Variational BNN with local reparameterization ref

Todo

Clean up and refactorize code for:

• Add GP and TGP
• Stochastic gradient MCMC ( Hamiltonian Monte Carlo ) BNN ref, for classification
• Point Estimate NN (should not go here but useful for comparison), for classification
• Probabilistic data augmentation using MCMC
• Probabilistic data augmentation with Mean Field VI (aka VAE)
• Probabilistic data augmentation with flows.
• Add regression example to the Bayesian NN models. The ones comparing MFVI and HMC