Search Results for author: Raffaele Paolino

Found 3 papers, 2 papers with code

Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning

1 code implementation20 Mar 2024 Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok

We introduce $r$-loopy Weisfeiler-Leman ($r$-$\ell{}$WL), a novel hierarchy of graph isomorphism tests and a corresponding GNN framework, $r$-$\ell{}$MPNN, that can count cycles up to length $r + 2$.

A Fractional Graph Laplacian Approach to Oversmoothing

1 code implementation NeurIPS 2023 Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok

In this paper, we generalize the concept of oversmoothing from undirected to directed graphs.

Unveiling the Sampling Density in Non-Uniform Geometric Graphs

no code implementations15 Oct 2022 Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie

A powerful framework for studying graphs is to consider them as geometric graphs: nodes are randomly sampled from an underlying metric space, and any pair of nodes is connected if their distance is less than a specified neighborhood radius.

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