1 citations · 1 across the 12 of their papers we have counts for
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Data-Driven Self-Supervised Graph Representation Learning
Ahmed E. Samy, Zekarias T. Kefatoa, Sarunas Girdzijauskasa
Self-supervised graph representation learning (SSGRL) is a representation learning paradigm used to reduce or avoid manual labeling. An essential part of SSGRL is graph data augmen…
Semi-decentralized Training of Spatio-Temporal Graph Neural Networks for Traffic Prediction
Ivan Kralj, Lodovico Giaretta, Gordan Ježić +2
In smart mobility, large networks of geographically distributed sensors produce vast amounts of high-frequency spatio-temporal data that must be processed in real time to avoid maj…
SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate
Yifei Jin, Ali Maatouk, Sarunas Girdzijauskas +3
Wireless ray-tracing (RT) is emerging as a key tool for three-dimensional (3D) wireless channel modeling, driven by advances in graphical rendering. Current approaches struggle to…
On the effects of similarity metrics in decentralized deep learning under distributional shift
Edvin Listo Zec, Tom Hagander, Eric Ihre-Thomason +1
Decentralized Learning (DL) enables privacy-preserving collaboration among organizations or users to enhance the performance of local deep learning models. However, model aggregati…
Are We Wasting Time? A Fast, Accurate Performance Evaluation Framework for Knowledge Graph Link Predictors
Filip Cornell, Yifei Jin, Jussi Karlgren +1
The standard evaluation protocol for measuring the quality of Knowledge Graph Completion methods - the task of inferring new links to be added to a graph - typically involves a ste…