2 citations · 2 across the 4 of their papers we have counts for
4 papers
Adaptive Reduced Multilevel Splitting
Frédéric Cérou, Patrick Héas, Mathias Rousset
This paper considers the classical problem of sampling with Monte Carlo methods a target rare event distribution defined by a score function that is very expensive to compute. We a…
3D wind field profiles from hyperspectral sounders: revisiting optic-flow from a meteorological perspective
P. Héas, O. Hautecoeur, R. Borde
In this work, we present an efficient optic flow algorithm for the extraction of vertically resolved 3D atmospheric motion vector (AMV) fields from incomplete hyperspectral image d…
Entropy minimizing distributions are worst-case optimal importance proposals
Frédéric Cérou, Patrick Héas, Mathias Rousset
Importance sampling of target probability distributions belonging to a given convex class is considered. Motivated by previous results, the cost of importance sampling is quantifie…
Chilled Sampling for Uncertainty Quantification: A Motivation From A Meteorological Inverse Problem
Patrick Héas, Frédéric Cérou, Mathias Rousset
Atmospheric motion vectors (AMVs) extracted from satellite imagery are the only wind observations with good global coverage. They are important features for feeding numerical weath…