AINeutralarXiv – CS AI · 10h ago6/10
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Forecasting Source Stability in Scientific Experiments using Temporal Learning Models: A Case Study from Tritium Monitoring
Researchers at the KATRIN experiment applied advanced deep learning models to predict source stability in tritium monitoring, identifying N-BEATS as the optimal forecasting algorithm. This application demonstrates how temporal learning models can optimize real-world physics experiments by improving measurement scheduling and maintenance planning through accurate long-horizon time-series predictions.