Physics-Informed multiple quantile regression for complex environmental data

Music City Center 

I will present a Physics-Informed multiple quantile regression model. The method features a regularizing term involving a Partial Differential Equation, that encodes the available problem-specific information about the phenomenon under study. The method permits to jointly estimate multiple quantiles, preserving monotonicity. Moreover, it can handle spatial data observed over non-Euclidean domains, such as linear networks, two-dimensional manifolds and non-convex volumes. The method will be illustrated through application to the study of nitrogen dioxide over Lombardy region, in Italy.

spatial data analysis

smoothing with roughness penalties

quantile regression 

IMS