Zobrazeno 1 - 10
of 64
pro vyhledávání: '"NECKEL, TOBIAS"'
Autor:
Ravi, Kislaya, Fediukov, Vladyslav, Dietrich, Felix, Neckel, Tobias, Buse, Fabian, Bergmann, Michael, Bungartz, Hans-Joachim
One of the main challenges in surrogate modeling is the limited availability of data due to resource constraints associated with computationally expensive simulations. Multi-fidelity methods provide a solution by chaining models in a hierarchy with i
Externí odkaz:
http://arxiv.org/abs/2404.11965
With the emergence of Artificial Intelligence, numerical algorithms are moving towards more approximate approaches. For methods such as PCA or diffusion maps, it is necessary to compute eigenvalues of a large matrix, which may also be dense depending
Externí odkaz:
http://arxiv.org/abs/2311.06115
Markov Chain Monte Carlo (MCMC) methods often take many iterations to converge for highly correlated or high-dimensional target density functions. Methods such as Hamiltonian Monte Carlo (HMC) or No-U-Turn Sampling (NUTS) use the first-order derivati
Externí odkaz:
http://arxiv.org/abs/2310.02703
Autor:
Farcas, Ionut-Gabriel, Peherstorfer, Benjamin, Neckel, Tobias, Jenko, Frank, Bungartz, Hans-Joachim
Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computati
Externí odkaz:
http://arxiv.org/abs/2211.10835
Publikováno v:
soon in Springer LNCS Series, Parallel Processing and Applied Mathematics 14th International Conference, PPAM 2022
Training deep neural networks consumes increasing computational resource shares in many compute centers. Often, a brute force approach to obtain hyperparameter values is employed. Our goal is (1) to enhance this by enabling second-order optimization
Externí odkaz:
http://arxiv.org/abs/2208.02017
Autor:
Konrad, Julia, Farcas, Ionut-Gabriel, Peherstorfer, Benjamin, Di Siena, Alessandro, Jenko, Frank, Neckel, Tobias, Bungartz, Hans-Joachim
Publikováno v:
J. Comput. Phys 451 (2022) 110898
The linear micro-instabilities driving turbulent transport in magnetized fusion plasmas (as well as the respective nonlinear saturation mechanisms) are known to be sensitive with respect to various physical parameters characterizing the background pl
Externí odkaz:
http://arxiv.org/abs/2103.07539
Autor:
Farcas, Ionut-Gabriel, Latz, Jonas, Ullmann, Elisabeth, Neckel, Tobias, Bungartz, Hans-Joachim
Publikováno v:
SIAM J. Sci. Comput. 42(1), pp. A424-A451, 2020
Deterministic interpolation and quadrature methods are often unsuitable to address Bayesian inverse problems depending on computationally expensive forward mathematical models. While interpolation may give precise posterior approximations, determinis
Externí odkaz:
http://arxiv.org/abs/1904.12204
Autor:
Farcaș, Ionuț-Gabriel, Peherstorfer, Benjamin, Neckel, Tobias, Jenko, Frank, Bungartz, Hans-Joachim
Publikováno v:
In Computer Methods in Applied Mechanics and Engineering 1 March 2023 406
Quantifying uncertainty in predictive simulations for real-world problems is of paramount importance - and far from trivial, mainly due to the large number of stochastic parameters and significant computational requirements. Adaptive sparse grid appr
Externí odkaz:
http://arxiv.org/abs/1812.00080