11:53

Part 45: fast and effective GNN training with linearized random spanning trees

11:09

Part 44: ASAP: adaptive structure aware pooling for learning hierarchical graph representation

9:11

Part 40: towards sparse hierarchical graph classifiers

23:19

Regime Switching Models with Machine Learning | Piotr Pomorski

15:18

Part 36: graph pooling for graph neural networks: progress, challenges, and opportunities

10:51

Matriz de confusión 6: Métricas ocultas de aprendizaje automático que no puedes permitirte ignorar

10:10

Part 47: graph clustering with graph neural networks

12:58

Part 42: grouping-matrix based graph pooling with adaptive number of clusters