EN.553.726 — Point Processes and Stochastic Geometry

Lecture notes by Eliza O'Reilly. Fall 2025.

  1. Lecture 1: What are Point Processes?
  2. Lecture 2: Intensity Measure and Campbell's Theorem
  3. Lecture 3: How to describe distribition of point processes?
  4. Lecture 4: Characterizing the Distribition of Point Processes
  5. Lecture 5: Poisson Processes
  6. Lecture 6: Poisson Processes Continued
  7. Lecture 7: More on Poisson Transformations
  8. Lecture 8: Markings and Stationairy
  9. Lecture 9: The Palm Distribution
  10. Lecture 10: Palm Distribution Continued
  11. Lecture 11: Cox Processes (Doubly Stochastic Poisson Processes)
  12. Lecture 12: Janossy Measures
  13. Lecture 13: Gibbs Point Processes (+ Intro to DPPs)
  14. Lecture 14: Determinantal Point Processes (DPPs)
  15. Lecture 15: Random Closed Sets
  16. Lecture 16: Random Closed Sets (Continued)
  17. Lecture 17: Set Processes
  18. Lecture 18: Particle Processes
  19. Lecture 19: Boolean Models and Random Voronoi Tessellations
  20. Lecture 20: Inversion Formula
  21. Lecture 21: Processes of Flats
  22. Lecture 22: Poisson Hyperplane Processes
  23. Lecture 23: Random Tessellations