GNN Analyses
[[lecture-main-topic-data]]
Concepts
Concepts
| File | status | type | Lectures |
|---|---|---|---|
| convergence in L-p implies convergence in cut norm | complete | 🧮 | |
| Convergence in the cut norm implies convergence in L2 | complete | 🧮 | |
| convergent graph sequence | complete | 💡 | |
| cut distance | in progress | 💡 | |
| cut norm | complete | 💡 | |
| fully random graph | complete | 💡 | |
| fully random graphs converge to the graphon in probability | complete | 💡 | |
| graph edit distance | complete | 💡 | |
| graph motif | complete | 💡 | |
| graph sequence converges if and only if the induced graphon sequence converges | complete | 🧮 | |
| graphon | in progress | 💡 | |
| graphon signal | complete | 💡 | |
| induced graphon | in progress | 💡 | |
| induced graphon signal | complete | 💡 | |
| kernel cut metric | in progress | 💡 | |
| kernel cut norm | complete | 💡 | |
| template graph | complete | 💡 | |
| template graphs converge to the graphon | complete | 🧮 | |
| ways to sample graphs from graphons | in progress | 💡 | |
| weighted graph (sample) | complete | 💡 | |
| weighted sampled graphs converge to the graphon in probability | 🧮 |
Mentions
Mentions
Created 2025-03-24 Last Modified 2025-05-13
