Projekteja vuodessa
Abstrakti
Graph pooling is a central component of a myriad of graph neural network (GNN) architectures. As an inheritance from traditional CNNs, most approaches formulate graph pooling as a cluster assignment problem, extending the idea of local patches in regular grids to graphs. Despite the wide adherence to this design choice, no work has rigorously evaluated its influence on the success of GNNs. In this paper, we build upon representative GNNs and introduce variants that challenge the need for locality-preserving representations, either using randomization or clustering on the complement graph. Strikingly, our experiments demonstrate that using these variants does not result in any decrease in performance. To understand this phenomenon, we study the interplay between convolutional layers and the subsequent pooling ones. We show that the convolutions play a leading role in the learned representations. In contrast to the common belief, local pooling is not responsible for the success of GNNs on relevant and widely-used benchmarks.
Alkuperäiskieli | Englanti |
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Otsikko | Advances in Neural Information Processing Systems 33 pre-proceedings (NeurIPS 2020) |
Tila | Julkaistu - 2020 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisuussa |
Tapahtuma | Conference on Neural Information Processing Systems - Virtual, Vancouver, Kanada Kesto: 6 joulukuuta 2020 → 12 joulukuuta 2020 Konferenssinumero: 34 |
Julkaisusarja
Nimi | Advances in neural information processing systems |
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Kustantaja | Morgan Kaufmann Publishers |
Vuosikerta | 33 |
ISSN (painettu) | 1049-5258 |
Conference
Conference | Conference on Neural Information Processing Systems |
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Lyhennettä | NeurIPS |
Maa/Alue | Kanada |
Kaupunki | Vancouver |
Ajanjakso | 06/12/2020 → 12/12/2020 |
Sormenjälki
Sukella tutkimusaiheisiin 'Rethinking pooling in graph neural networks'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.-
FCAI: Suomen tekoälykeskus
01/01/2019 → 31/12/2022
Projekti: Academy of Finland: Other research funding
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Interaktiivinen koneoppiminen useista biodatalähteistä
Jälkö, J., Hegde, P., Kaski, S., Gadd, C., Jain, A., Hämäläinen, A., Siren, J., Shen, Z. & Trinh, T.
01/01/2019 → 31/08/2021
Projekti: Academy of Finland: Other research funding
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Interaktiivinen koneoppiminen useista biodatalähteistä
01/01/2016 → 31/08/2021
Projekti: Academy of Finland: Other research funding