Random Networks, Nutshellfully
A brief reprise of the imagined pure random networks, and their very useful extension to allow for arbitrary degree distributions.
Reheated slides on toast:
60M
; Last updated: 2025/01/11, 13:46:55
Freeze-dried snack slides:
5.0M
; Last updated: 2025/01/11, 13:45:51
Original slides as served in lectures:
61M
; Last updated: 2025/01/11, 13:44:20
Covered in these episode(s) and clip(s):
Clip 1: Random Networks intro (6:43)
Clip 2: Construction methods 1/2 (6:32)
Clip 3: Visual examples of random networks (7:37)
Clip 4: Phase transition: The appearance of the Giant Component (2:42)
Clip 5: Clustering = 0 for random networks (3:04)
Clip 6: Pure random networks have Poission degree distributions (6:16)
Clip 7: Generalized random networks, or The Configuration Model (6:10)
Clip 8: Construction methods 2/2 (6:23)
Clip 9: Motifs (2:43)
Clip 10: Edge-degree distribution (11:44)
Clip 11: Upsettingly strange friends (4:39)
Clip 12: The giant component condition for random networks (7:23)
Clip 13: A better spreading condition (9:40)
Clip 14: Erdős–Rényi networks: Giant component condition (1:14)
Clip 15: Scale-free networks: Giant component condition (5:02)