wl44-li / vb_dlm

Variational Bayesian Inference on Dynamic Linear Model

VB_DLM

Variational Bayesian Inference for Dynamic Linear Model

Important: Work in Progress

• For latest supported features, please refer to the development branch
• Under development:
  • Convergence check,
  • Overfitting test,
  • Integration with Turing.jl

Setup and Installation

You need to install Julia (1.9) and then Pluto to run the notebook.

Alternatively, static html files are availble for general browsing using any internet browser.

Usage

On your command prompt or terminal:

julia
               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.9.0 (2023-05-07)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |

julia> using Pluto

julia> Pluto.run()
[ Info: Loading...
┌ Info: 
└ Opening http://localhost:1234/?secret=$$$$$ in your default browser... ~ have fun!
┌ Info: 
│ Press Ctrl+C in this terminal to stop Pluto
└ 

Pluto should launch on your default browser, you can then use it to open the designated notebook file (i.e. vbem_dlm.jl).

Credits

This work was inspired by or uses the following sources:

• Beal, Matthew J. (2003). Variational Algorithm for Approximate Bayesian Inference. UCL.