Advanced Machine Learning: Deep Generative Models

What it is about

You will engage with advanced methods of machine learning, with a focus on deep generative models. In the end you will know the theoretical foundations and be able to apply and implement the key building blocks (Normalizing Flows, VAEs, GANs, diffusion models) in a modern programming language and qualitatively compare them.

What you will be able to do

• Understand theoretical foundations of advanced ML principles
• Identify core components of generative models
• Implement learning algorithms in a programming language
• Compare and evaluate methods based on qualitative properties

What the module consists of

• VorlesungDelivery of theoretical concepts using slides
• Interaktive Tutorials/DemonstrationenPractical exercise of concepts and clarification of properties
• Aufgaben / ProgrammierübungenDeepening of knowledge through individual work and implementation

Teaching method

• Vorlesung mit PräsentationsfolienDiscussion of theoretical concepts
• Interaktive Tutorials und DemonstrationenPractical application and illustration of properties
• Assignments (Einzelarbeit) mit ProgrammieraufgabenIndependent practice and implementation experience