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We introduce a nonparametric approach for estimating drift and diffusion functions in systems of stochastic differential equations from observations of the state vector.
The choice of a class interval
H.A. Sturges · 1926
Earlier work this paper cites.
Deterministic nonperiodic flow
Edward N Lorenz · 1963
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Probability, random variables, and stochastic processes
Athanasios Papoulis · 1965
Earlier work this paper cites.
Maximum likelihood from incomplete data via the em algorithm
Arthur P Dempster, Nan M Laird, and Donald B Rubin · 1977
Earlier work this paper cites.
Handbook of Stochastic Methods
C. W. Gardiner · 1996
Earlier work this paper cites.
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Lehel Csató, Manfred Opper, and Ole Winther · 2002
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Sparse on-line gaussian processes
Lehel Csató and Manfred Opper · 2002
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Numerical techniques for maximum likelihood estimation of continuous-time diffusion processes
Garland B Durham and A Ronald Gallant · 2002
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Fully nonparametric estimation of scalar diffusion models
Federico M. Bandi and Peter C. B. Phillips · 2003
Earlier work this paper cites.
High-resolution record of northern hemisphere climate extending into the last interglacial period
Katrine K Andersen, N Azuma, J-M Barnola, Matthias Bigler, P Biscaye, N Caillon, J Chappellaz, Henrik Brink Clausen, Dorthe Dahl-Jensen, Hubertus Fischer, et al · 2004
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Gaussian Processes for Machine Learning
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Simulation and Inference for Stochastic Differential Equations: With R Examples (Springer Series in Statistics)
Stefano M. Iacus · 2008
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Variational inference for diffusion processes
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Steven J. Lade · 2009
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Variational learning of inducing variables in sparse Gaussian processes
Numerical Solution of Stochastic Differential Equations
P. E. Kloeden and E. Platen · 2011
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Nonparametric estimation of diffusions: a differential equations approach
Omiros Papaspiliopoulos, Yvo Pokern, Gareth O. Roberts, and Andrew M. Stuart · 2012
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Posterior consistency via precision operators for Bayesian nonparametric drift estimation in SDEs
Yvo Pokern, Andrew M. Stuart, and J.H. van Zanten · 2013
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Approximate gaussian process inference for the drift function in stochastic differential equations
Andreas Ruttor, Philipp Batz, and Manfred Opper · 2013
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Analysis and modelling of glacial climate transitions using simple dynamical systems
Frank Kwasniok · 2013
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Monte Carlo statistical methods
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Andrew Golightly and Darren J Wilkinson · 2010
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Frank van der Meulen, Moritz Schauer, and Harry van Zanten · 2014
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Variational mean-field algorithm for efficient inference in large systems of stochastic differential equations
Michail D. Vrettas, Dan Cornford, and Manfred Opper · 2015
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Philipp Batz, Andreas Ruttor, and Manfred Opper · 2016
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