A federated graph learning method to realize multi-party collaboration for molecular discovery
LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).Article Google Scholar Abramson, J. et al. Accurate...
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Adaptive Adjustment Graph Representation Learning Method for Rotating Machinery Fault Diagnosis Under Noisy Signals
Newswise — In the field of rotating machinery fault diagnosis, intelligent fault diagnosis methods based on graph neural networks (GNNs)...
Prototype based contrastive graph clustering network for reducing false negatives
This section introduces the proposed prototype-driven contrastive graph clustering network, as shown in Fig. 1. The network consists of two...
Simulation of personalized english learning path recommendation system based on knowledge graph and deep reinforcement learning
This study proposes an online personalized English learning path recommendation method that integrates knowledge graphs with deep reinforcement learning, aiming...
A hybrid reinforcement learning and knowledge graph framework for financial risk optimization in healthcare systems
This section presents the architecture, learning framework, and overall workflow of the proposed hybrid reinforcement learning and knowledge graph-based system...
Adaptive Adjustment Graph Representation Learning Method for Rotating Machinery Fault Diagnosis Under Noisy Signals
Newswise — In recent years, intelligent fault diagnosis methods have been applied to the condition monitoring of rotating machinery. Among...
