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Mathematics and Machine Learning
Abstract
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Next lectures
16.12.2024, 15:00 (E2 10 (Leon-Lichtenstein))
13.01.2025, 14:00 (E2 10 (Leon-Lichtenstein))
20.01.2025, 14:00 (E2 10 (Leon-Lichtenstein))
27.01.2025, 14:00 (E2 10 (Leon-Lichtenstein))
03.02.2025, 14:00 (E2 10 (Leon-Lichtenstein))
10.02.2025, 14:00 (E2 10 (Leon-Lichtenstein))
17.02.2025, 14:00 (E2 10 (Leon-Lichtenstein))
24.02.2025, 14:00 (E2 10 (Leon-Lichtenstein))
03.03.2025, 14:00 (E2 10 (Leon-Lichtenstein))
10.03.2025, 14:00 (E2 10 (Leon-Lichtenstein))
17.03.2025, 14:00 (E2 10 (Leon-Lichtenstein))
24.03.2025, 14:00 (E2 10 (Leon-Lichtenstein))
This weekly lecture series will cover topics at the intersection of mathematics and machine learning, running from November 4, 2024, to March 24, 2025.
Topics include:
- Deep learning (brief introduction)
- Convolutional neural networks
- Autoencoders
- LLMs for code generation
- Foundations of feature learning
- Geometric and topological deep learning
- Dynamical systems and machine learning
- Varieties and machine learning, with applications to computer vision and biology
Lecturers: Paul Breiding, Marzieh Eidi, Jan Ewald, Robert Hasse, Parvaneh Joharinad, Duc Luu, Guido Montufar, Nico Scherf, Diaaeldin Taha, Angelica Torres.
Organizers: Parvaneh Joharinad, Diaaeldin Taha.
Keywords
mathematics and machine learning
Audience
Students and researchers in Math and/or CS
Language
English