Recently, contrastive learning approaches have achieved significant empirical success in representation learning for multivariate time series classification (MTSC). A key component of contrastive ...
Overcoming Data Scarcity at the Edge: A Federated Learning Approach with GAN-Based Data Augmentation
Abstract: Renewable energy forecasting—particularly for distributed solar power—is vital for ensuring grid reliability and efficient resource management. However, traditional centralized forecasting ...
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