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Authors: Pedro H. C. Avelar 1 ; Anderson R. Tavares 1 ; Marco Gori 2 and Luís C. Lamb 1

Affiliations: 1 Institute of Informatics, Federal University of Rio Grande do Sul - UFRGS, Porto Alegre, Brazil ; 2 Department of Computing, University of Siena, Siena, Italy

Keyword(s): Graph Neural Networks, Residual Learning.

Abstract: We propose the use of continuous residual modules for graph kernels in Graph Neural Networks. We show how both discrete and continuous residual layers allow for more robust training, being that continuous residual layers are applied by integrating through an Ordinary Differential Equation (ODE) solver to produce their output. We experimentally show that these modules achieve better results than the ones with non-residual modules when multiple layers are used, thus mitigating the low-pass filtering effect of Graph Convolutional Network-based models. Finally, we discuss the behaviour of discrete and continuous residual layers, pointing out possible domains where they could be useful by allowing more predictable behaviour under dynamic times of computation.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Avelar, P.; Tavares, A.; Gori, M. and Lamb, L. (2021). Discrete and Continuous Deep Residual Learning over Graphs. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 119-131. DOI: 10.5220/0010231501190131

@conference{icaart21,
author={Pedro H. C. Avelar. and Anderson R. Tavares. and Marco Gori. and Luís C. Lamb.},
title={Discrete and Continuous Deep Residual Learning over Graphs},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={119-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010231501190131},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - Discrete and Continuous Deep Residual Learning over Graphs
SN - 978-989-758-484-8
IS - 2184-433X
AU - Avelar, P.
AU - Tavares, A.
AU - Gori, M.
AU - Lamb, L.
PY - 2021
SP - 119
EP - 131
DO - 10.5220/0010231501190131
PB - SciTePress

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