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Kernel-based Prediction of Non-Markovian Time Series
A nonparametric method to predict non-Markovian time series of partially...
07/08/2020 ∙ by Faheem Gilani, et al. ∙
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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...
06/07/2020 ∙ by Shixiao W. Jiang, et al. ∙
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Bridging data science and dynamical systems theory
This short review describes mathematical techniques for statistical anal...
02/18/2020 ∙ by Tyrus Berry, et al. ∙
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Kernel Embedding Linear Response
In the paper, we study the problem of estimating linear response statist...
12/23/2019 ∙ by He Zhang, et al. ∙
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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...
10/30/2019 ∙ by He Zhang, et al. ∙
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Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
This paper investigates the formulation and implementation of Bayesian i...
10/23/2019 ∙ by John Harlim, et al. ∙
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Machine Learning for Prediction with Missing Dynamics
This article presents a general framework for recovering missing dynamic...
10/13/2019 ∙ by John Harlim, et al. ∙
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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...
05/17/2019 ∙ by Shixiao W. Jiang, et al. ∙
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