Posterior consistency for Gaussian process approximations of Bayesian posterior distributions von STUART, ANDREW M., TECKENTRUP, ARETHA L.

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Gaussian processes for Bayesian inverse problems associated with linear partial differential equations von Bai, Tianming, Teckentrup, Aretha L., Zygalakis, Konstantinos C.

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Bayesian comparison of stochastic models of dispersion von Brolly, Martin T., Maddison, James R., Teckentrup, Aretha L., Vanneste, Jacques

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Convergence of Gaussian Process Regression with Estimated Hyper-Parameters and Applications in Bayesian Inverse Problems von Teckentrup, Aretha L.

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Adaptive Multilevel Monte Carlo for Probabilities von Haji-Ali, Abdul-Lateef, Spence, Jonathan, Teckentrup, Aretha L.

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Data Assimilation – Mathematical Foundation and Applications von Marzouk, Youssef M., Reich, Sebastian, Teckentrup, Aretha

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Smoothed Circulant Embedding with Applications to Multilevel Monte Carlo Methods for PDEs with Random Coefficients von Istratuca, Anastasia, Teckentrup, Aretha

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Introduction to Gaussian Process Regression in Bayesian Inverse Problems, with New Results on Experimental Design for Weighted Error Measures von Helin, Tapio, Stuart, Andrew M., Teckentrup, Aretha L., Zygalakis, Konstantinos C.

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A multilevel stochastic collocation method for SPDEs von Gunzburger, Max, Jantsch, Peter, Teckentrup, Aretha, Webster, Clayton

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Multilevel Monte Carlo methods for highly heterogeneous media von Teckentrup, A. L.

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Error Bounds for Some Approximate Posterior Measures in Bayesian Inference von Lie, Han Cheng, Sullivan, T. J., Teckentrup, Aretha

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Deep Gaussian Process Priors for Bayesian Image Reconstruction von Latz, Jonas, Teckentrup, Aretha L, Urbainczyk, Simon

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Posterior Consistency for Gaussian Process Approximations of Bayesian Posterior Distributions von Stuart, Andrew M, Teckentrup, Aretha L

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Smoothed Circulant Embedding with Applications to Multilevel Monte Carlo Methods for PDEs with Random Coefficients von Istratuca, Anastasia, Teckentrup, Aretha

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Convergence rates of non-stationary and deep Gaussian process regression von Moriarty-Osborne, Conor, Teckentrup, Aretha L

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Convergence of Gaussian Process Regression with Estimated Hyper-parameters and Applications in Bayesian Inverse Problems von Teckentrup, Aretha L

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Gaussian processes for Bayesian inverse problems associated with linear partial differential equations von Bai, Tianming, Teckentrup, Aretha L, Zygalakis, Konstantinos C

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Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures von Helin, Tapio, Stuart, Andrew, Teckentrup, Aretha, Zygalakis, Konstantinos

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Deep Gaussian Process Priors for Bayesian Image Reconstruction von Latz, Jonas, Teckentrup, Aretha L, Urbainczyk, Simon

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Probabilistic Richardson Extrapolation von Oates, Chris. J, Karvonen, Toni, Teckentrup, Aretha L, Strocchi, Marina, Niederer, Steven A

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