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Einblick - Graph Neural Networks (GNNs)
Eine kritische Betrachtung der Bewertung von GNNs unter Heterophilie
Standard-GNNs übertreffen spezialisierte Modelle bei der Bewertung unter Heterophilie.
LMC: Fast Training of GNNs via Subgraph-wise Sampling with Provable Convergence at ICLR 2023
Local Message Compensation (LMC) is a subgraph-wise sampling method with provable convergence, accelerating training efficiency for GNNs.
K-Link: Knowledge-Link Graph from LLMs for Enhanced Representation Learning in Multivariate Time-Series Data
Large Language Models (LLMs) enhance graph quality for Multivariate Time-Series (MTS) data representation learning.
GraphEdit: Large Language Models for Graph Structure Learning
Large language models can enhance graph structure learning by denoising noisy connections and uncovering implicit node-wise dependencies.
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