Probabilistic Graphical Models:

  Principles and Applications

  
Professor:
Luis Enrique Sucar
esucar (AT) inaoep.mx


Text Book

L. E. Sucar, Probabilistic Graphical Models: Principles and Applications, Springer 2015


General Description

Program


Calendar

Class Sessions


Course Notes

Class 1 - Introduction [PDF]
Class 2 - Probability [PDF]
Class 3 - Graphs [PDF]
Class 4 - Bayesian classifiers [PDF]
Class 5 - Hidden Markov Models [PDF]
Class 6 - Markov Random Fields [PDF]
Class 7 - Bayesian networks: representation and inference [Part I - PDF] [Part II - PDF]
Class 8 - Bayesian networks: learning [PDF]
Class 9 - Dynamic and Temporal Bayesian Networks [PDF]
Class 10 - Decision Graphs [PDF]
Class 11 - Markov Decision Processes [PDF]
Class 12 - Relational Probabilistic Graphical Models [PDF]
Class 13 - Causal Graphical Models [PDF]


Previous Notes (in Spanish)

Clase 1: Introducción [PDF]
Clase 2: Probabilidad [PDF]
Clase 3: Teoría de Información [PDF]
Clase 4: Grafos [PDF]
Clase 5: Métodos Básicos [PDF]
Ejemplos Excel [Ej1] [Ej2]
Clase 6: Clasificadores [PDF] [Imprimible]
Ejemplos Excel [Ej3]
Clase 7: Modelos Ocultos de Markov [PDF] [Imprimible]
Clase 8: Campos de Markov [PDF] [Imprimible]
Clase 9: Redes Bayesianas - Representación [PDF] [Imprimible]
Clase 10: Redes Bayesianas - Inferencia (Parte I) [PDF] [Imprimible]
Clase 11: Redes Bayesianas - Inferencia (Parte II) [PDF] [Imprimible]
Clase 12: Redes Bayesianas - Aprendizaje [PDF] [Imprimible]
Clase 13: Redes Bayesianas - Extensiones y Aplicaciones [PDF]
Clase 14: Redes de Decisión [PDF]
Clase 15: Procesos de Decisión de Markov [PDF]
Clase 16: Alternativas y Extensiones [PDF]


Homework

Week
1:
Week 2:
Week 3:
Week 4:
Week 5/6:
Week 7:
Week 8:

Week 9:
Week 10:
Week 11:
Week 12:
Week 13:



FINAL PROJECT



References

Philosofical aspects

Reasoning under uncertainty

Probabilistic graphical models
Markov chains and HMMs Bayesian Networks
MDPs and POMDPs UAI

Tools


Other external links

Software/Data:

Associations: Conferences:

    Uncertainty in AI
    Probabilistic Graphical Models:
    FLAIRS - Uncertain Reasoning Track:
Bayesian Networks:
Projects

Projects suggestions:
Previous projects:



Resumen [PDF] [PPTX]