1 code implementation • 21 Apr 2023 • Andrea Cavallo, Claas Grohnfeldt, Michele Russo, Giulio Lovisotto, Luca Vassio
Yet, achievement of consistent GNN performance on heterophilous graphs remains an open research problem.
Ranked #7 on Node Classification on Cornell
Node Classification on Non-Homophilic (Heterophilic) Graphs Representation Learning
no code implementations • 26 Dec 2022 • Andrea Cavallo, Claas Grohnfeldt, Michele Russo, Giulio Lovisotto, Luca Vassio
In this work, we highlight the limitations of the widely used homophily ratio and the recent Cross-Class Neighborhood Similarity (CCNS) metric in estimating GNN performance.
no code implementations • 3 Aug 2017 • Andrea Zunino, Jacopo Cavazza, Atesh Koul, Andrea Cavallo, Cristina Becchio, Vittorio Murino
In this paper, we bridge cognitive and computer vision studies, by demonstrating the effectiveness of video-based approaches for the prediction of human intentions.
no code implementations • 31 May 2016 • Andrea Zunino, Jacopo Cavazza, Atesh Koul, Andrea Cavallo, Cristina Becchio, Vittorio Murino
In this paper, we address the new problem of the prediction of human intents.