15 citations · 20 across the 5 of their papers we have counts for
5 papers
Posterior contraction rates for non-parametric state and drift estimation
Sebastian Reich, Paul Rozdeba
We consider a combined state and drift estimation problem for the linear stochastic heat equation. The infinite-dimensional Bayesian inference problem is formulated in terms of the…
State and Parameter Estimation from Observed Signal Increments
Nikolas Nüsken, Sebastian Reich, Paul J. Rozdeba
The success of the ensemble Kalman filter has triggered a strong interest in expanding its scope beyond classical state estimation problems. In this paper, we focus on continuous-t…
Machine Learning of Time Series Using Time-delay Embedding and Precision Annealing
Alexander J. A. Ty, Zheng Fang, Rivver A. Gonzalez +2
Tasking machine learning to predict segments of a time series requires estimating the parameters of a ML model with input/output pairs from the time series. Using the equivalence b…
Machine Learning as Statistical Data Assimilation
H. D. I. Abarbanel, P. J. Rozdeba, S. Shirman
We identify a strong equivalence between neural network based machine learning (ML) methods and the formulation of statistical data assimilation (DA), known to be a problem in stat…
Machine Learning, Deepest Learning: Statistical Data Assimilation Problems
Henry Abarbanel, Paul Rozdeba, Sasha Shirman
We formulate a strong equivalence between machine learning, artificial intelligence methods and the formulation of statistical data assimilation as used widely in physical and biol…