3 papers
stat.ML2026
A Distribution-to-Distribution Neural Probabilistic Forecasting Framework for Dynamical Systems
Tianlin Yang, Hailiang Du, Louis Aslett
Probabilistic forecasting provides a principled framework for uncertainty quantification in dynamical systems by representing predictions as probability distributions rather than d…
stat.ML2024
Holdouts set for safe predictive model updating
Sami Haidar-Wehbe, Samuel R Emerson, Louis J M Aslett +1
Predictive risk scores for adverse outcomes are increasingly crucial in guiding health interventions. Such scores may need to be periodically updated due to change in the distribut…
cs.LG2024
Ethical considerations of use of hold-out sets in clinical prediction model management
Louis Chislett, Louis JM Aslett, Alisha R Davies +2
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential inte…