02901 Advanced Topics in Machine Learning: Tensor Networks for Machine Learning

August 24-28, 2026

Description

The course consists of five days of lectures, exercises, and presentations. The lectures will cover theoretical and practical aspects of tensor networks for machine learning. Technical aspects, programming and application of the covered concepts will be explored in tutorials and exercises. The course (2.5 ECTS points) passed by handing in a small report covering topics in the course. For further course details click here.

Location

TBA

Confirmed Speakers

Mahito Sugiyama, associate professor, National Institute of Informatics, Japan.

Evrim Acar, Chief Research Scientist/Research Professor, Simula Metropolitan, Oslo, Norway.

Antonio Vergari , Associate Professor, University of Edinburgh, UK.

Beatriz Quintanilla Casas, Assistant Professor, Department of Food Science, Copenhagen University.

Michael Kastoryano , associate Professor, Department of Computer-science, Copenhagen University.

Tentative Course Programme (subject to changes)

Monday

Introduction to tensors and tensor networks.
Applications of tensor decompositions to life science data.

Tuesday

Supervised and Reinforcement learning using tensor networks.
Tensor networks for science.

Wednesday

Deep learning and tensor networks.

Thursday

Probabilistic circuits and tensor networks.
Tensor networks, divergences and deformed algebra for probability estimation.

Friday

Information geometry and tensors.
Project work and closing remarks.

Requirements

General understanding of machine learning, statistical modeling, mathematics and computer science. Programming experience, ideally in Python. For the course you are required to bring your own laptop computer.

Application and Registration

To registrer please send a CV to kazfu@dtu.dk no later than the 14th of June 2026. Confirmations will be sent out by the 27th of June.

After receiving a positive confirmation on the application, registration in DTUs systems must be carried out. For academics (masters and PhD students) there is no registration fee for the course. Students affiliated with DTU can use the course planner to register. PhD students outside of DTU have register via here. For all other participants a course fee will be charged and apart from signing up additional registration must be completed here.