Course Syllabus for

Introduction to Optimal Transport
Introduktion till optimal transport

FRT305F, 4 credits

Valid from: Autumn 2023
Decided by: Maria Sandsten
Date of establishment: 2023-09-12

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English


Optimal transport is a ubiquitous tool in various applications, such as image processing, machine learning and natural science. The course aims at giving a quick introduction to the fundamental theories of optimal transport, to help the students be able to do use optimal transport in their research work.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must be able to solve optimal transport problems using numerical methods.

Course Contents

- fundamental theories of optimal transport, e.g., Kantorovich and Monge problems, structure of minimizers, Wasserstein spaces, geodesic structures, etc., - efficient numerical methods for computing optimal transport, e.g. Brenier-Benamou formula (continuous OT) and entropy regularization (discrete OT), - some applications, e.g., Beckman's problem, image processing.

Course Literature

Instruction Details

Type of instruction: Lectures

Examination Details

Examination format: Written report
Grading scale: Failed, pass
Examiner: Postdoctoral fellow Dongjun Wu

Admission Details

Admission requirements: Probability
Minimum number of participants: 7

Course Occasion Information

Start date: 2024-01-01. Start date is approximate.
End date: 2024-03-01
Course pace: Full time

Contact and Other Information

Course coordinators:

Web page:

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