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University of Gothenburg
Mathematical Structures of Deep Neural Networks
The goal of this course is to give an overview of the mathematical structures that appear in modern deep neural networks and enable students to understand current research literature in the field. To this end, the course starts with a concise introduction to the field of deep learning followed by deeper dives into t…
- Higher education
- Information unavailable
- 19 January 2026
- Information unavailable
- Information unavailable
- 50 %
Overview
The goal of this course is to give an overview of the mathematical structures that appear in modern deep neural networks and enable students to understand current research literature in the field. To this end, the course starts with a concise introduction to the field of deep learning followed by deeper dives into the topics of equivariant neural networks, large width neural networks and geometrical aspects of explainable AI. The lectures are accompanied by computer labs where students learn the basics of implementing neural networks.
Admission scores
Entry requirements
General entry requirements and the equivalent of the courses MSG110 Probability Theory, MVG301 Programming with Python, and MMG500 Algebraic Structures. In addition to these requirements, it is also desirable with knowledge corresponding to the courses DIT013 Imperative Programming with Basic Object Orientation, MMA211 Higher Differential Calculus, and MMA201 Representation Theory.
The text is reproduced from the Susa source. Antagningsdata does not map GY11 and GY25 or assess personal eligibility.
Source, measure and data quality
- Source
- Skolverket Susa-navet
- Period
- 2026-01-19
- Measure
- Entry-requirement text reproduced from the published Susa data; no personal eligibility assessment is made.
- Population
- Education offering e.uoh.gu.mma440.17056.20261
- Last checked
- 2026-09-23T10:36:59.285029+00:00
- Limitation
- Antagningsdata does not map GY11 and GY25. General and specific conditions are not separated without structured source data.
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- Programme or course starts
- Programme or course ends
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About the provider
Sources and data quality
Education facts for the selected offering come from Skolverket Susa-navet.
Retrieved . Published . Times are shown in Swedish local time.
Source identity and publication version
- Publication version
- 8e217193-f5fa-4778-b085-a4521fd03e8d
- Education identity in the source
- i.uoh.gu.mma440.17056.20261
- Offering identity in the source
- e.uoh.gu.mma440.17056.20261
- Education-form source code
- HS
- Education code in the source
- MMA440
- Change time according to the source
- 2026-01-22T12:47:34
The provider, education and education offering are separate identities. Application information should be checked on the official website. Supplementary statistics have not been obtained from this source.