ESE Ph.D. Thesis Defense: “Machine Learning on Large-Scale Graphs”
Room 452 C, 3401 Walnut 3401 Walnut Street, Philadelphia, PA, United StatesGraph neural networks (GNNs) are successful at learning representations from most types of network data but suffer from limitations in large graphs, which do not have the Euclidean structure that time and image signals have in the limit. Yet, large graphs can often be identified as being similar to each other in the sense that […]