The analysis of household resilience to food insecurity has become a key technical and evidence-based policy instrument for better tailoring development and humanitarian intervention designs. International development agencies must strengthen the capacity of vulnerable households to anticipate,...

The method of predicting events based on correlation mapping and Fourier decomposition of relevant time series, which is presented in this paper, is intended for the predictive calculation of signs that an event will occur. As input data for calculating the forecast, in addition to the series...

We develop a distribution regression model under endogenous sample selection. This model is a semi-parametric generalization of the Heckman selection model. It accommodates much richer effects of the covariates on outcome distribution and patterns of heterogeneity in the selection process, and...

This work presents a set of neural network (NN) models specifically designed for accurate and efficient fluid dynamics forecasting. In this work, we show how neural networks training can be improved by reducing data complexity through a modal decomposition technique called higher order dynamic...