A problem-oriented taxonomy groups anomaly detection metrics into six dimensions and experiments show that some popular ones like NAB and Point-Adjust fail to resist random-score inflation.
A multimodal anomaly detector for robot-assisted feeding using an lstm-based variational autoencoder
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Experiments on real industrial time series show that partial model sharing improves diffusion model performance in bandwidth-limited non-IID settings, while full sharing stabilizes GAN training but offers less robustness than VAE or DDPM alternatives.
citing papers explorer
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A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection
A problem-oriented taxonomy groups anomaly detection metrics into six dimensions and experiments show that some popular ones like NAB and Point-Adjust fail to resist random-score inflation.
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On the Tradeoffs of On-Device Generative Models in Federated Predictive Maintenance Systems
Experiments on real industrial time series show that partial model sharing improves diffusion model performance in bandwidth-limited non-IID settings, while full sharing stabilizes GAN training but offers less robustness than VAE or DDPM alternatives.