Optimal acquisition functions for active learning of pdf tails
T. Sapsis, A. Blanchard, Optimal criteria and their asymptotic form for data selection in data-driven reduced-order modeling with Gaussian process regression, Philosophical Transactions of the Royal Society A [pdf]

Active learning with neural operators to quantify extreme events
E. Pickering et al., Discovering and forecasting extreme events via active learning in neural operators, Nature Computational Science [pdf]

A review of methods for modeling of extremes in fluids
T. Sapsis, Statistics of extreme events in fluid flows and waves, Annual Review of Fluid Mechanics [pdf]

Physically consistent NN closures for UQ of turbulent flows
A. Charalampopoulos, T. Sapsis, Uncertainty quantification of turbulent systems via physically consistent and data-informed reduced-order models, Physics of Fluids [pdf]