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Pere Barlet-Ros

2 accepted papers

2026

GraphUniverse: Enabling Systematic Evaluation of Inductive Generalization

ICLR 2026poster

A fundamental challenge in graph learning is understanding how models generalize to new, unseen graphs. While synthetic benchmarks offer controlled settings for analysis, existing approaches are confined to single-graph, transductive settings where models train and test on the same graph structure.…

Cited by 0SourcecodeScholar
2022

FlowDT: A Flow-Aware Digital Twin for Computer Networks

ICASSP 2022accepted

Network modeling is an essential tool for network planning and management. It allows network administrators to explore the performance of new protocols, mechanisms, or optimal configurations without the need for testing them in real production networks. Recently, Graph Neural Networks (GNNs) have em…

Cited by 0SourceScholar