Link Prediction for Flow-Driven Spatial Networks

Bastian Wittmann, Johannes C. Paetzold, Chinmay Prabhakar, Daniel Rueckert, Bjoern Menze

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

3 Zitate (Scopus)

Abstract

Link prediction algorithms aim to infer the existence of connections (or links) between nodes in network-structured data and are typically applied to refine the connectivity among nodes. In this work, we focus on link prediction for flow-driven spatial networks, which are embedded in a Euclidean space and relate to physical exchange and transportation processes (e.g., blood flow in vessels or traffic flow in road networks). To this end, we propose the Graph Attentive Vectors (GAV) link prediction framework. GAV models simplified dynamics of physical flow in spatial networks via an attentive, neighborhood-aware message-passing paradigm, updating vector embeddings in a constrained manner. We evaluate GAV on eight flow-driven spatial networks given by whole-brain vessel graphs and road networks. GAV demonstrates superior performances across all datasets and metrics and outperformed the state-of-the-art on the ogbl-vessel benchmark at the time of submission by 12% (98.38 vs. 87.98 AUC). All code is publicly available on GitHub https://github.com/bwittmann/GAV.

OriginalspracheEnglisch
TitelProceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten2460-2469
Seitenumfang10
ISBN (elektronisch)9798350318920
DOIs
PublikationsstatusVeröffentlicht - 2024
Veranstaltung2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 - Waikoloa, USA/Vereinigte Staaten
Dauer: 4 Jan. 20248 Jan. 2024

Publikationsreihe

NameProceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024

Konferenz

Konferenz2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024
Land/GebietUSA/Vereinigte Staaten
OrtWaikoloa
Zeitraum4/01/248/01/24

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