Bo-Wei Yang

Benchmark-grounded self-supervised contrastive learning for AMI-based distribution grid monitoring

Introduction Self-supervised contrastive learning is effective for time-series representation learning, but its deployment in industrial environments remains challenging because of spatiotemporal heterogeneity, domain-specific noise, and label scarcity. We study these challenges in the smart-grid domain, a representati...