49 citations · 89 across the 6 of their papers we have counts for
8 papers
Adaptive tempering schedules with approximative intermediate measures for filtering problems
Iris Rammelmüller, Gottfried Hastermann, Jana de Wiljes
Data assimilation algorithms integrate prior information from numerical model simulations with observed data. Ensemble-based filters, regarded as state-of-the-art, are widely emplo…
A Bayesian Approach to Atmospheric Circulation Regime Assignment
Swinda K. J. Falkena, Jana de Wiljes, Antje Weisheimer +1
The standard approach when studying atmospheric circulation regimes and their dynamics is to use a hard regime assignment, where each atmospheric state is assigned to the regime it…
Randomized maximum likelihood based posterior sampling
Yuming Ba, Jana de Wiljes, Dean S. Oliver +1
Minimization of a stochastic cost function is commonly used for approximate sampling in high-dimensional Bayesian inverse problems with Gaussian prior distributions and multimodal…
Reconstructing regime-dependent causal relationships from observational time series
Elena Saggioro, Jana de Wiljes, Marlene Kretschmer +1
Inferring causal relations from observational time series data is a key problem across science and engineering whenever experimental interventions are infeasible or unethical. Incr…
Interacting particle filters for simultaneous state and parameter estimation
Angwenyi David, Jana de Wiljes, Sebastian Reich
Simultaneous state and parameter estimation arises from various applicational areas but presents a major computational challenge. Most available Markov chain or sequential Monte Ca…
Kalman Filter and its Modern Extensions for the Continuous-time Nonlinear Filtering Problem
Amirhossein Taghvaei, Jana de Wiljes, Prashant G. Mehta +1
This paper is concerned with the filtering problem in continuous-time. Three algorithmic solution approaches for this problem are reviewed: (i) the classical Kalman-Bucy filter whi…
Long-time stability and accuracy of the ensemble Kalman-Bucy filter for fully observed processes and small measurement noise
Jana de Wiljes, Sebastian Reich, Wilhelm Stannat
The ensemble Kalman filter has become a popular data assimilation technique in the geosciences. However, little is known theoretically about its long term stability and accuracy. I…
Second-order accurate ensemble transform particle filters
Walter Acevedo, Jana de Wiljes, Sebastian Reich
Particle filters (also called sequential Monte Carlo methods) are widely used for state and parameter estimation problems in the context of nonlinear evolution equations. The recen…