10 citations · 27 across the 8 of their papers we have counts for
11 papers
Copula Active Subspaces II: Error Decomposition, A Posteriori Estimation, and Sharpness of the Bounds
Joshua Chen, Peter Jan van Leeuwen
The Copula Active Subspaces (CAS) method of Part I estimates a non-Gaussian observation-noise density from residual samples. Its KL divergence $\mathcal{D}_{\m…
Copula Active Subspaces I: A Score-Covariance Method for Reduced-Order Non-Gaussian Density Estimation
Joshua Chen, Peter Jan van Leeuwen
In Bayesian inference problems with non-Gaussian observation noise, the posterior is only as accurate as the noise density, and gradient-based samplers need that density and its gr…
From Variational Optimization to Flow-Based Transport: Posterior-Geometry Regularization for Ill-Conditioned Data Assimilation
Siming Liang, Feng Bao, Hristo G. Chipilski +2
Variational data assimilation computes a Bayesian update through optimization on a fixed posterior geometry, whose conditioning is determined by the prior covariance and the observ…
Noise calibration for the stochastic rotating shallow water model
Dan Crisan, Oana Lang, Alexander Lobbe +2
Stochastic partial differential equations have been used in a variety of contexts to model the evolution of uncertain dynamical systems. In recent years, their applications to geop…
Particle Filtering and Gaussian Mixtures -- On a Localized Mixture Coefficients Particle Filter (LMCPF) for global NWP
Anne Rojahn, Nora Schenk, Peter Jan van Leeuwen +1
In a global numerical weather prediction (NWP) modeling framework we study the implementation of Gaussian uncertainty of individual particles into the assimilation step of a locali…
Bayesian Inference for Fluid Dynamics: A Case Study for the Stochastic Rotating Shallow Water Model
Peter Jan van Leeuwen, Dan Crisan, Oana Lang +1
In this work, we use a tempering-based adaptive particle filter to infer from a partially observed stochastic rotating shallow water (SRSW) model which has been derived using the S…
Using Mutual Information to measure Time-lags from non-linear processes in Astronomy
Nachiketa Chakraborty, Peter Jan van Leeuwen
Measuring time lags between time-series or lighcurves at different wavelengths from a variable or transient source in astronomy is an essential probe of physical mechanisms causing…
A Framework for Causal Discovery in non-intervenable systems
Peter Jan van Leeuwen, Michael DeCaria, Nachiketa Chakaborty +1
Many frameworks exist to infer cause and effect relations in complex nonlinear systems but a complete theory is lacking. A new framework is presented that is fully nonlinear, provi…
Ensemble Riemannian Data Assimilation over the Wasserstein Space
Sagar K. Tamang, Ardeshir Ebtehaj, Peter J. Van Leeuwen +2
In this paper, we present an ensemble data assimilation paradigm over a Riemannian manifold equipped with the Wasserstein metric. Unlike the Eulerian penalization of error in the E…
Massively Parallel Implicit Equal-Weights Particle Filter for Ocean Drift Trajectory Forecasting
Håvard Heitlo Holm, Martin Lilleeng Sætra, Peter Jan van Leeuwen
Forecasting ocean drift trajectories are important for many applications, including search and rescue operations, oil spill cleanup and iceberg risk mitigation. In an operational s…
Kernel embedding of maps for sequential Bayesian inference: The variational mapping particle filter
Manuel Pulido, Peter Jan vanLeeuwen
In this work, a novel sequential Monte Carlo filter is introduced which aims at efficient sampling of high-dimensional state spaces with a limited number of particles. Particles ar…