Adrien Petralia

Outperforming traditional model selection, a retrieval-based approach finds the best anomaly detector for unseen time series by leveraging similarity to past data, even in challenging OOD scenarios.

LoaDiff is introduced, a diffusion-based generative model for year-long, sub-hourly smart-meter load curves that generates realistic and diverse load profiles, achieves a favorable trade-off between generation quality and limited evidence of memorization, and preserves information useful for downstream energy applications.