The content of this repository served as an assignment project requested for the course Probabilistic Graphical Models at the INAOE as a student of the Master in Science in Computer Science. All the resources presented in the versions of this code were obtained from the class book that you can find in the references part.
This application of the algorithm and information was for an only educational purpose
Implement the stochastic simulation algorithm for obtaining the most probable configuration of a 1st order regular MRF considering the at least two variantes ICM and Metropolis, using MAP.Professor:
- PhD Enrique Sucar.
Student Involved:
- Mario De Los Santos. Github: MarSH-Up. Email: madlsh3517@gmail.com
Instructions
- Download the repository's file
- Verify that the C++ version is at least C++ 14
- Call the functions marked in the documentation
Example
We run some examples, you can find the document here, the idea is give you a more detail approach to the replication, also, in the images folder you can find the exercise used. The following exercise if also in the documentation folder.
The next figures, shows the implementation using the two methods in the class, MAP and Metroplis.
#References
- Sucar, L. E. (2020). Probabilistic graphical models. Advances in Computer Vision and Pattern Recognition.London: Springer London. doi, 10(978), 2
#Licence: GNU GENERAL PUBLIC LICENSE Version 3