Arrival, Breakfast, Registration

• Troels Petersen (Niels Bohr Institute)

Room: Auditorium A

Scope of School and Lecture 1: Introduction and overview of Machine Learning

• Troels Petersen (Niels Bohr Institute)

Room: Auditorium A

Lecture 2: Basics of Machine Learning & Fast Data Loaders

• Troels Petersen (Niels Bohr Institute)
• Inar Timiryasov (NBI)

Room: Auditorium A

Discussion of Lectures and Introduction to exercises

• Daniel Murnane (Niels Bohr Institute, University of Copenhagen)

Room: K-building, floor E (top floor)

Work on exercises

• Daniel Murnane (Niels Bohr Institute, University of Copenhagen)
• Troels Petersen (Niels Bohr Institute)
• Rasmus Ørsøe (TUM)

Room: K-building, floor E (top floor)

Work on exercises

• Daniel Murnane (Niels Bohr Institute, University of Copenhagen)
• Troels Petersen (Niels Bohr Institute)
• Rasmus Ørsøe (TUM)

Room: K-building, floor E (top floor)

Lecture 3: Networks with Learned Uncertainties

• Tilman Plehn (Heidelberg University)

Room: Auditorium A All my lectures will be on the blackboard, based on the published Heidelberg lecture notes. Tutorials maintained by the Heidelberg group are linked in the lecture notes.

Lecture 4: Generative Networks and Classifier Tests

• Tilman Plehn (Heidelberg University)

Room: Auditorium A

Discussion of Lectures and intro to exercises Room: Auditorium A

Work on exercises Room: Auditorium A

Work on exercises Room: Auditorium A

Lecture 5: Modern Generative Networks

• Tilman Plehn (Heidelberg University)

Room: Auditorium A

Lecture 6: Probabilistic regression with generative models

• Malte Algren

Room: Auditorium A

Discussion of Lectures and intro to exercises Room: Auditorium A

Work on exercises Room: Auditorium A

Train ride to Helsingør, visit to Kronborg Castle, drinks on the ramparts, and dinner at Værftets Madmarket. Room: Auditorium A

Lecture 7: Anomaly Detection

• Thea Aarrestad (ETH Zurich)

Room: Auditorium A

Lecture 8: Network optimisation and fast inference

• Thea Aarrestad (ETH Zurich)

Room: Auditorium A

Work on exercises and own projects Room: Auditorium A

Work on exercises and own projects Room: Auditorium A

Lecture 9: Transformers and Foundation Models

• Malte Algren

Room: Auditorium A

Lecture 10: Domain shifts and Past experiences

• Troels Petersen (Niels Bohr Institute)

Room: Auditorium A

Discussion of Lectures Room: Auditorium A

Exchange of experiences, resources, and "tricks" Room: Auditorium A

Presentation of projects over drinks and snacks Room: Auditorium A