3 papers
cs.LG2025
iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
Nicolas Lell, Ansgar Scherp
Shallow node embeddings like node2vec (N2V) can be used for nodes without features or to supplement existing features with structure-based information. Embedding methods like N2V a…
cs.LG2024
HyperAggregation: Aggregating over Graph Edges with Hypernetworks
Nicolas Lell, Ansgar Scherp
HyperAggregation is a hypernetwork-based aggregation function for Graph Neural Networks. It uses a hypernetwork to dynamically generate weights in the size of the current neighborh…
cs.LG2024
Lifelong Graph Learning for Graph Summarization
Jonatan Frank, Marcel Hoffmann, Nicolas Lell +2
Summarizing web graphs is challenging due to the heterogeneity of the modeled information and its changes over time. We investigate the use of neural networks for lifelong graph su…