On posterior consistency of data assimilation with Gaussian process priors: the 2D-Navier-Stokes equations
DOI10.1214/24-aos2427MaRDI QIDQ6621548
Publication date: 18 October 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
posterior distributionnonlinear dynamical systemprior distributionlogarithmic estimateBayesian inference for the initial condition
Gaussian processes (60G15) Asymptotic properties of nonparametric inference (62G20) Navier-Stokes equations for incompressible viscous fluids (76D05) Navier-Stokes equations (35Q30) Existence problems for PDEs: global existence, local existence, non-existence (35A01) Uniqueness problems for PDEs: global uniqueness, local uniqueness, non-uniqueness (35A02) Strong solutions to PDEs (35D35)
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Cites Work
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- Bayesian inverse problems with non-conjugate priors
- Spectral gaps for a Metropolis-Hastings algorithm in infinite dimensions
- Bayesian inverse problems with Gaussian priors
- On statistical Calderón problems
- Bernstein-von Mises theorems for statistical inverse problems. I: Schrödinger equation
- Geometric MCMC for infinite-dimensional inverse problems
- Statistical guarantees for Bayesian uncertainty quantification in nonlinear inverse problems with Gaussian process priors
- Nonparametric Bayesian inference for reversible multidimensional diffusions
- Nonparametric statistical inference for drift vector fields of multi-dimensional diffusions
- Stability of the non-abelian \(X\)-ray transform in dimension \(\ge 3\)
- Dimension-independent likelihood-informed MCMC
- Sur l'unicité retrograde des équations paraboliques et quelques questions voisines
- On Bayesian consistency for flows observed through a passive scalar
- Sparse deterministic approximation of Bayesian inverse problems
- Inverse problems: A Bayesian perspective
- Mathematical Foundations of Infinite-Dimensional Statistical Models
- Bayesian inverse problems for functions and applications to fluid mechanics
- Deterministic Nonperiodic Flow
- Bayesian Recovery of the Initial Condition for the Heat Equation
- Convergence Rates for Penalized Least Squares Estimators in PDE Constrained Regression Problems
- Consistent Inversion of Noisy <scp>Non‐Abelian X‐Ray</scp> Transforms
- Stability estimate for the broken non-abelian x-ray transform in Minkowski space
- Consistency of Bayesian inference with Gaussian process priors for a parabolic inverse problem
- Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
- Probabilistic Forecasting and Bayesian Data Assimilation
- Data Assimilation
- Filtering Complex Turbulent Systems
- Fundamentals of Nonparametric Bayesian Inference
- MCMC methods for functions: modifying old algorithms to make them faster
- Bayesian non-linear statistical inverse problems
- On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
- Consistent inference for diffusions from low frequency measurements
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