5 papers
Improving Long-Range Interactions in Graph Neural Simulators via Hamiltonian Dynamics
Tai Hoang, Alessandro Trenta, Alessio Gravina +4
Learning to simulate complex physical systems from data has emerged as a promising way to overcome the limitations of traditional numerical solvers, which often require prohibitive…
Non-Dissipative Graph Propagation for Non-Local Community Detection
William Leeney, Alessio Gravina, Davide Bacciu
Community detection in graphs aims to cluster nodes into meaningful groups, a task particularly challenging in heterophilic graphs, where nodes sharing similarities and membership…
Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks
Ali Hariri, Álvaro Arroyo, Alessio Gravina +6
ChebNet, one of the earliest spectral GNNs, has largely been overshadowed by Message Passing Neural Networks (MPNNs), which gained popularity for their simplicity and effectiveness…
GRAMA: Adaptive Graph Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni +3
Graph State Space Models (SSMs) have recently been introduced to enhance Graph Neural Networks (GNNs) in modeling long-range interactions. Despite their success, existing methods e…
ECLYPSE: a Python Framework for Simulation and Emulation of the Cloud-Edge Continuum
Jacopo Massa, Valerio De Caro, Stefano Forti +3
The Cloud-Edge continuum enhances application performance by bringing computation closer to data sources. However, it presents considerable challenges in managing resources and det…