Course - Geometric Deep Learning HT26

Created: October 10, 2025 | Updated: October 15, 2025 | About these notes | View in context | Study these flashcards

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• Course Webpage
• Lecture Notes (old)
  • 1, Introduction
  • 2, ML in high dimensions
  • 3+4, Geometric priors
  • 5, Sets
  • 6+7, Graphs
  • 8, Graph foundation models
  • 9+10, Grids
  • 11, Groups and homogenous spaces
  • 12, Geometric graphs and geometrics GNNs
  • 13, Manifolds
  • 14, Gauges
  • 15, Spectral methods
  • 16, Physics-inspired methods
• Lecture recordings
  • 2024-2025
  • 2025-2026
• Other resources:
  • Mathematical Background for GDL
  • Equivariant and coordinate independent convolutional networks
• Other courses this term: [[Courses HT26]]^U

Notes

Problem Sheets

• Sheet 1, [[Problem Sheet - Geometric Deep Learning HT256, I]]^?
• Sheet 2, [[Problem Sheet - Geometric Deep Learning HT256, II]]^?

To-Do List

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