From the 1 of 8 linked papers with an AI index.
1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
Hyperbolic Graph Embedders for Link Prediction and Topology Reconstruction
Robert Jankowski, Maksim Kitsak, Dorota Celińska-Kopczyńska
Hyperbolic embeddings provide compact geometric representations of complex networks in hyperbolic spaces, but systematic comparisons of methods developed in machine learning, netwo…
Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization
Robert Jankowski, Pedro Almagro-Blanco, Marián Boguñá +2
The paper proposes training graph neural networks on geometrically renormalized, coarse‑grained versions of a graph and then directly applying the learned weights to the original f…
Task complexity shapes internal representations and robustness in neural networks
Robert Jankowski, Filippo Radicchi, M. Ãngeles Serrano +2
Neural networks excel across a wide range of tasks, yet remain black boxes. In particular, how their internal representations are shaped by the complexity of the input data and the…
Hyperbolic Benchmarking Unveils Network Topology-Feature Relationship in GNN Performance
Roya Aliakbarisani, Robert Jankowski, M. Ãngeles Serrano +1
Graph Neural Networks (GNNs) have excelled in predicting graph properties in various applications ranging from identifying trends in social networks to drug discovery and malware d…