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Kernel-based Prediction of Non-Markovian Time Series
A nonparametric method to predict non-Markovian time series of partially...
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Ghost Point Diffusion Maps for solving elliptic PDE's on Manifolds with Classical Boundary Conditions
In this paper, we extend the class of kernel methods, the so-called diff...
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Bridging data science and dynamical systems theory
This short review describes mathematical techniques for statistical anal...
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Kernel Embedding Linear Response
In the paper, we study the problem of estimating linear response statist...
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Linear Response Based Parameter Estimation in the Presence of Model Error
Recently, we proposed a method to estimate parameters in stochastic dyna...
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Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
This paper investigates the formulation and implementation of Bayesian i...
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Machine Learning for Prediction with Missing Dynamics
This article presents a general framework for recovering missing dynamic...
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Modeling of Missing Dynamical Systems: Deriving Parametric Models using a Nonparametric Framework
In this paper, we consider modeling missing dynamics with a non-Markovia...
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