Bayesian Machine Learning

My experiments in Bayesian Machine Learning. I make use of pyro's ppl constructs for building models and inference (pyro.infer.SVI). Every experiment is in a separate folder with documentation in README. The list of experiments are given below.

• [x] Deconstructing Pyro
• [x] Bayesian Linear Regression
  • [x] Multivariate Linear Regression
• [x] Bayesian Logistic Regression
  • [x] Binary Classification
  • [x] Multiclass Classification
  • [x] MNIST Classification
• [ ] Bayes by Backprop
  • [x] Bayesian Neural Network for MNIST Classification
  • [ ] Out-of-domain Uncertainty
• [ ] Bayesian Neural Network
• [ ] Bayesian Convolutional Neural Network
• [x] Gaussian Mixture Model
• [ ] Pyro Demystified
• [ ] Introduction to PyMC3
• [x] Gaussian Processes
  • [x] GPytorch
  • [ ] Simulation of Bose Einstein Condensates with Gaussian Processes

Related Work

• Anatomy of Probabilistic Programming Languages

How to Contribute?

Would you like a question (relevant to Bayes ML) answered? Rise an issue and I'll add an experiment to answer it (if necessary).