I have started reading on MRF and CRF in a short-term duration; however, I have a lot of difficulty in understanding the concepts. Can anyone suggest some online resources for theoretical and basic understanding? I have a lot of difficulty in understanding maths of these two concepts.
Besides, I would like to try and see each stages of these two graphical models during implementation to get better understanding for further implementation and utilisation. Is there any practical tutorial on this area which is being implemented in Matlab/ other programming languages?
I will be thankful if someone knows, please guide me since I am quite confused and do not know how to start from beginning.
Your help will be appreciated. Thanks...
A number of graphical model inference methods are implemented in Matlab here: https://github.com/johannesu/meanfield-matlab
Another graphical model toolbox for Matlab is: https://people.cs.umass.edu/~domke/JGMT/
If you are interested in Computer Vision, the code for the well-known DenseCRF model was released by the author: http://graphics.stanford.edu/projects/densecrf/
Code for Graph-cut based inference of CRFs has also been released by authors: http://vision.csd.uwo.ca/code/ and http://research.microsoft.com/en-us/um/people/pkohli/code.html
The following Coursera online course may help with general understanding, and implementing graphical models yourself: https://www.coursera.org/learn/probabilistic-graphical-models