6.4k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH70 papers
- Centre de Recherche en Économie et StatistiqueFR4 papers
- Max Planck Institute for Intelligent SystemsDE4 papers
- University of ZurichCH4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- University of BernCH3 papers
- Carnegie Mellon UniversityUS2 papers
- Delft University of TechnologyNL2 papers
- Heidelberg UniversityDE2 papers
- Institute for Biomedical EngineeringCH2 papers
- Laboratoire d’Analyse et de Mathématiques AppliquéesFR2 papers
- Ludwig-Maximilians-Universität MünchenDE2 papers
6 papers · 1 filter
Particle filters for high-dimensional geoscience applications: a review
Peter Jan van Leeuwen, Hans R. Künsch, Lars Nerger +2
Particle filters contain the promise of fully nonlinear data assimilation. They have been applied in numerous science areas, but their application to the geosciences has been limit…
Hierarchical inference for genome-wide association studies: a view on methodology with software
Claude Renaux, Laura Buzdugan, Markus Kalisch +1
We provide a view on high-dimensional statistical inference for genome-wide association studies (GWAS). It is in part a review but covers also new developments for meta analysis wi…
A local ensemble transform Kalman particle filter for convective scale data assimilation
Sylvain Robert, Daniel Leuenberger, Hans R. Künsch
Ensemble data assimilation methods such as the Ensemble Kalman Filter (EnKF) are a key component of probabilistic weather forecasting. They represent the uncertainty in the initial…
Localizing the Ensemble Kalman Particle Filter
Sylvain Robert, Hans R. Künsch
Ensemble methods such as the Ensemble Kalman Filter (EnKF) are widely used for data assimilation in large-scale geophysical applications, as for example in numerical weather predic…
MissForest - nonparametric missing value imputation for mixed-type data
Daniel J. Stekhoven, Peter Bühlmann
Modern data acquisition based on high-throughput technology is often facing the problem of missing data. Algorithms commonly used in the analysis of such large-scale data often dep…
A dynamic nonstationary spatio-temporal model for short term prediction of precipitation
Fabio Sigrist, Hans R. Künsch, Werner A. Stahel
Precipitation is a complex physical process that varies in space and time. Predictions and interpolations at unobserved times and/or locations help to solve important problems in m…