324 citations · 484 across the 31 of their papers we have counts for
37 papers
CRPS-Based Targeted Sequential Design with Application in Chemical Space
Lea Friedli, Athénaïs Gautier, Anna Broccard +1
Sequential design of real and computer experiments via Gaussian Process (GP) models has proven useful for parsimonious, goal-oriented data acquisition purposes. In this work, we fo…
Efficient pooling of predictions via kernel embeddings
Sam Allen, David Ginsbourger, Johanna Ziegel
Probabilistic predictions are probability distributions over the set of possible outcomes. Such predictions quantify the uncertainty in the outcome, making them essential for effec…
Easy Conditioning far beyond Gaussian
Antoine Faul, David Ginsbourger, Ben Spycher
Multivariate Gaussian distributions enjoy Gaussian conditional distributions that makes conditioning easy: conditioning boils down to implementing analytical formulae for condition…
Non-Sequential Ensemble Kalman Filtering using Distributed Arrays
Cédric Travelletti, Jörg Franke, David Ginsbourger +1
This work introduces a new, distributed implementation of the Ensemble Kalman Filter (EnKF) that allows for non-sequential assimilation of large datasets in high-dimensional proble…
Consistency of some sequential experimental design strategies for excursion set estimation based on vector-valued Gaussian processes
Philip Stange, David Ginsbourger
We tackle the extension to the vector-valued case of consistency results for Stepwise Uncertainty Reduction sequential experimental design strategies established in [Bect et al., A…
An energy-based model approach to rare event probability estimation
Lea Friedli, David Ginsbourger, Arnaud Doucet +1
The estimation of rare event probabilities plays a pivotal role in diverse fields. Our aim is to determine the probability of a hazard or system failure occurring when a quantity o…