Probabilistic Graphical Models are a core technology for machine learning, decision making, computer vision, natural language processing and many other artificial intelligence applications. In this subject, we provide an overview of the topic. We review the formal theoretical foundations and we study how to put them in practice in order to solve problems of your interest.
Person in charge
Jerónimo Hernández González (
Generic Technical Competences
CG3 - Capacity for modeling, calculation, simulation, development and implementation in technology and company engineering centers, particularly in research, development and innovation in all areas related to Artificial Intelligence.
Technical Competences of each Specialization
CEA3 - Capability to understand the basic operation principles of Machine Learning main techniques, and to know how to use on the environment of an intelligent system or service.
CEA8 - Capability to research in new techniques, methodologies, architectures, services or systems in the area of ??Artificial Intelligence.
CEA12 - Capability to understand the advanced techniques of Knowledge Engineering, Machine Learning and Decision Support Systems, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEA13 - Capability to understand advanced techniques of Modeling , Reasoning and Problem Solving, and to know how to design, implement and apply these techniques in the development of intelligent applications, services or systems.
CEP1 - Capability to solve the analysis of information needs from different organizations, identifying the uncertainty and variability sources.
CEP2 - Capability to solve the decision making problems from different organizations, integrating intelligent tools.
CEP3 - Capacity for applying Artificial Intelligence techniques in technological and industrial environments to improve quality and productivity.
CEP5 - Capability to design new tools and new techniques of Artificial Intelligence in professional practice.
CT4 - Capacity for managing the acquisition, the structuring, analysis and visualization of data and information in the field of specialisation, and for critically assessing the results of this management.
CT6 - Capability to evaluate and analyze on a reasoned and critical way about situations, projects, proposals, reports and scientific-technical surveys. Capability to argue the reasons that explain or justify such situations, proposals, etc..
Analisis y sintesis
CT7 - Capability to analyze and solve complex technical problems.
CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
CB9 - Possession of the learning skills that enable the students to continue studying in a way that will be mainly self-directed or autonomous.
Lectures dynamically combine master explanations and problem solving. The weekly schedule of in-person activities is distributed in three hours. Some slots may be exclusively dedicated to programming throughout directed activities or notebooks.
The students will be required to present an application of PGMs (their own or other people's) to problems of their interest, or a recently proposed PGM technique.