
Scaling Graphbased Deep Learning models to larger networks
Graph Neural Networks (GNN) have shown a strong potential to be integrat...
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Describing Subjective Experiment Consistency by pValue PP Plot
There are phenomena that cannot be measured without subjective testing. ...
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Deep Reinforcement Learning meets Graph Neural Networks: An optical network routing use case
Recent advances in Deep Reinforcement Learning (DRL) have shown a signif...
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RouteNet: Leveraging Graph Neural Networks for network modeling and optimization in SDN
Network modeling is a key enabler to achieve efficient network operation...
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Generalized Score Distribution
A class of discrete probability distributions contains distributions wit...
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Notation for Subject Answer Analysis
It is believed that consistent notation helps the research community in ...
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Unveiling the potential of Graph Neural Networks for network modeling and optimization in SDN
Network modeling is a critical component for building selfdriving Softw...
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MessagePassing Neural Networks Learn Little's Law
The paper presents a solution to the problem of universal representation...
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Krzysztof Rusek
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