[PDF] Top 20 Uncertainty quantification in high dimensional problems
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Uncertainty quantification in high dimensional problems
... space.Sample space.Sample ([space, data, plabels, …]) Container class for samples.. space.Space space.Space (corners[, sample, nrefine, …]) Manages the space of parameters.[r] ... Voir le document complet
216
Uncertainty quantification on pareto fronts and high-dimensional strategies in bayesian optimization, with applications in multi-objective automotive design
... illustrated in Figure ...intrusion in case of a shock and in particular the deformation of the underlying metallic structure in low speed impact scenarii ...ECE42. In the considered ... Voir le document complet
205
Fundamental performance limits for ideal decoders in high-dimensional linear inverse problems
... interpreted in our framework, and possibly be generalized to other types of signals? Task-oriented decoders versus general purpose ...set-ups, in medical imaging and audio source separation, where only ... Voir le document complet
37
2020 — Deep learning methods for high-dimensional fluid dynamics problems : application to flood modeling with uncertainty quantification
... breakthroughs in sequenced ...Networks, in the context of Deep Learning, had been predicted for a long time, especially in Rina Dechter (1986), the community had to wait till the early 2010s to ... Voir le document complet
150
Anderson Localization in high dimensional lattices
... Open problems 21 I.9 Open problems After almost sixty years, the study of Anderson Localization remains an interesting and active field, with various open ...seen in section ( ...happens in ... Voir le document complet
197
Probabilistic numerical methods for high-dimensional stochastic control and valuation problems on electricity markets
... compute in practice the price of a forward contract on ...derivatives. In the literature on power price modeling, for both reduced-form models as well as structural models, being able to obtain closed-form ... Voir le document complet
188
Uncertainty quantification in system-level prognostics: application to Tennessee Eastman process
... on uncertainty intervals is performed by considering the α-accuracy metric, which determines whether a prediction falls within an α% ...interval. In fact, α-accuracy is a useful metric to judge if one ... Voir le document complet
7
Infarct localization from myocardial deformation: Prediction and uncertainty quantification by regression from a low-dimensional space
... and uncertainty quantification by regression from a low-dimensional space Nicolas Duchateau, Mathieu De Craene, Pascal Allain, Eric Saloux, Maxime Sermesant Abstract—Diagnosing and localizing ... Voir le document complet
14
Sparse Low Rank Approximation of Multivariate Functions – Applications in Uncertainty Quantification
... for high dimensional ...encountered in practical applications are found to have sufficiently accurate low rank representations and hence can be parametrized with few parameters in appropriate ... Voir le document complet
128
Active set strategy for high-dimensional non-convex sparse optimization problems
... on high dimensional data. In this work we express the optimality conditions of the optimization problem for a large class of non-convex ...gain in computa- tional cost ... Voir le document complet
6
Data driven uncertainty quantification in macroscopic traffic flow models
... consisting in hyperbolic partial differential equations based on the mass conservation principle, are employed since several decades to describe the spatio- temporal evolution of traffic aggregate quantities such ... Voir le document complet
25
Satellite Orbits in the Atmosphere: Uncertainty Quantification, Propagation and Optimal Control
... oblateness in Leonard's method [Bevilacqua and Romano, ...solution in a high-precision propagator [Kumar and Ng, 2008], and they highlighted the importance of accurate relative states estimation ... Voir le document complet
204
Adaptive unscented transform for uncertainty quantification in EMC large-scale systems
... Stochastic, Uncertainty, Unscented Transform INTRODUCTION The recent development of computational tools for electromagnetic compatibility allows accurate simulations of large-scale EMC ... Voir le document complet
3
Inverse uncertainty quantification applied to thermal-hydraulic simulations
... Bibliography Barbillon, Pierre ; Barthélémy, C. S. A. (2017). Parameter estimation of complex mixed models based on meta-model approach. Statistics and Computing, 27. Bousquet, N. and Blazère, M. (2016). Predicted ... Voir le document complet
29
A priori tensor approximations for the numerical solution of high dimensional problems: alternative definitions
... proposed in [15] in order to improve convergence properties of progressive PGD with respect to a spec- ified ...linear problems formulated in tensor product ... Voir le document complet
20
State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems
... Development history of particle filters Particle filters, like ensemble Kalman filters, are variants of Monte Carlo methods in which the probability distribution of the model state given [r] ... Voir le document complet
44
Sensitivity analysis and uncertainty quantification for environmental models
... or in storage capacity). In these cases, a preliminary step, which is less time consuming but also less informative, is ...focus in this paper on the method of screening introduced in ... Voir le document complet
23
Sensitivity analysis and uncertainty quantification for environmental models
... or in storage capacity). In these cases, a preliminary step, which is less time consuming but also less informative, is ...focus in this paper on the method of screening introduced in ... Voir le document complet
23
Uncertainty quantification in virtual surgery hemodynamics predictions for single ventricle palliation.
... target uncertainty is assessed, Bayesian parameter estimation (discussed in a clinical context in Section ...scarcity. In other words, equally likely solutions to a given problem may arise, ... Voir le document complet
30
Uncertainty quantification of thermo-acoustic instabilities in annular combustors
... 14.8% in the weakly coupled case and 39.5% in the strongly coupled ...very high growth rate variations compared with the weakly coupled regime (σ strongly ∼ 4σ weakly ... Voir le document complet
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