Search Results - "ULLMANN, ELISABETH"

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    Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems by KUO, FRANCES Y., SCHEICHL, ROBERT, SCHWAB, CHRISTOPH, SLOAN, IAN H., ULLMANN, ELISABETH

    Published in Mathematics of computation (01-11-2017)
    “…multilevel Quasi-Monte Carlo finite element discretisations and give a constructive proof of the dimension-independent convergence of the QMC rules. More…”
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    EP-PINNs: Cardiac Electrophysiology Characterisation Using Physics-Informed Neural Networks by Herrero Martin, Clara, Oved, Alon, Chowdhury, Rasheda A, Ullmann, Elisabeth, Peters, Nicholas S, Bharath, Anil A, Varela, Marta

    Published in Frontiers in cardiovascular medicine (03-02-2022)
    “…Accurately inferring underlying electrophysiological (EP) tissue properties from action potential recordings is expected to be clinically useful in the…”
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    Uncertainty quantification analysis of bifurcations of the Allen–Cahn equation with random coefficients by Kuehn, Christian, Piazzola, Chiara, Ullmann, Elisabeth

    Published in Physica. D (01-12-2024)
    “…In this work we consider the Allen–Cahn equation, a prototypical model problem in nonlinear dynamics that exhibits bifurcations corresponding to variations of…”
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    Fast sampling of parameterised Gaussian random fields by Latz, Jonas, Eisenberger, Marvin, Ullmann, Elisabeth

    “…Gaussian random fields are popular models for spatially varying uncertainties, arising for instance in geotechnical engineering, hydrology or image processing…”
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    Multilevel Sequential2 Monte Carlo for Bayesian inverse problems by Latz, Jonas, Papaioannou, Iason, Ullmann, Elisabeth

    Published in Journal of computational physics (01-09-2018)
    “…The identification of parameters in mathematical models using noisy observations is a common task in uncertainty quantification. We employ the framework of…”
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    Multilevel Sequential^sup 2^ Monte Carlo for Bayesian inverse problems by Latz, Jonas, Papaioannou, Iason, Ullmann, Elisabeth

    Published in Journal of computational physics (01-09-2018)
    “…The identification of parameters in mathematical models using noisy observations is a common task in uncertainty quantification. We employ the framework of…”
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    Journal Article
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    Bayesian inference with subset simulation in varying dimensions applied to the Karhunen–Loève expansion by Uribe, Felipe, Papaioannou, Iason, Latz, Jonas, Betz, Wolfgang, Ullmann, Elisabeth, Straub, Daniel

    “…Uncertainties associated with spatially varying parameters are modeled through random fields discretized into a finite number of random variables. Standard…”
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    Uncertainty quantification analysis of bifurcations of the Allen--Cahn equation with random coefficients by Kuehn, Christian, Piazzola, Chiara, Ullmann, Elisabeth

    Published 06-04-2024
    “…In this work we consider the Allen--Cahn equation, a prototypical model problem in nonlinear dynamics that exhibits bifurcations corresponding to variations of…”
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    Journal Article
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    Asymptotic Analysis of Multilevel Best Linear Unbiased Estimators by Schaden, Daniel, Ullmann, Elisabeth

    Published 07-12-2020
    “…We study the computational complexity and variance of multilevel best linear unbiased estimators introduced in [D. Schaden and E. Ullmann, SIAM/ASA J. Uncert…”
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    Consensus-based rare event estimation by Althaus, Konstantin, Papaioannou, Iason, Ullmann, Elisabeth

    Published 18-04-2023
    “…In this paper, we introduce a new algorithm for rare event estimation based on adaptive importance sampling. We consider a smoothed version of the optimal…”
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    Expansion of random field gradients using hierarchical matrices by Busch, Ingolf, Ernst, Oliver G., Ullmann, Elisabeth

    “…We present two expansions for the gradient of a random field. In the first approach, we differentiate its truncated Karhunen‐Loève expansion. In the second…”
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    The ensemble Kalman filter for rare event estimation by Wagner, Fabian, Papaioannou, Iason, Ullmann, Elisabeth

    Published 18-06-2021
    “…We present a novel sampling-based method for estimating probabilities of rare or failure events. Our approach is founded on the Ensemble Kalman filter (EnKF)…”
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    Certified and fast computations with shallow covariance kernels by Kressner, Daniel, Latz, Jonas, Massei, Stefano, Ullmann, Elisabeth

    Published 12-11-2020
    “…Foundations of Data Science 2(4): 487-512, 2020 Many techniques for data science and uncertainty quantification demand efficient tools to handle Gaussian…”
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    Error analysis for probabilities of rare events with approximate models by Wagner, Fabian, Latz, Jonas, Papaioannou, Iason, Ullmann, Elisabeth

    Published 14-08-2020
    “…The estimation of the probability of rare events is an important task in reliability and risk assessment. We consider failure events that are expressed in…”
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