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Titlebook: Neural-Symbolic Learning and Reasoning; 18th International C Tarek R. Besold,Artur d’Avila Garcez,Benedikt Wagn Conference proceedings 2024

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Towards Understanding the Impact of Graph Structure on Knowledge Graph Embeddingsrediction using KG embeddings (KGE). In this paper, we modify FB15k-237 in several ways (e.g., by increasingly including semantic metadata). This significantly changes the graph structure (e.g., centrality). We assess how these changes impact the link prediction task, using six KGE models.
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Logic Supervised Learning for Time Series - Continual Learning for Appliance Detectionters implausible results out which is helpful for productive usage, on the other hand these post processed results can be used to retrain the network and adapt it for a specific household in a continual learning process.
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