Process-Informed Forecasting models incorporating deterministic production recipe priors outperform ARIMA and deep learning baselines in accuracy, physical plausibility, and noise resilience for temperature forecasting in pharmaceutical lyophilization.
Pourkamali-Anaraki, Kolmogorov-arnold networks in low-data regimes: A comparative study with multilayer perceptrons, arXiv preprint arXiv:2409.10463 (2024)
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Process-Informed Forecasting of Complex Thermal Dynamics in Pharmaceutical Manufacturing
Process-Informed Forecasting models incorporating deterministic production recipe priors outperform ARIMA and deep learning baselines in accuracy, physical plausibility, and noise resilience for temperature forecasting in pharmaceutical lyophilization.