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[PDF][PDF] Fast numerical methods for stochastic computations: a review
This paper presents a review of the current state-of-the-art of numerical methods for
stochastic computations. The focus is on efficient high-order methods suitable for practical …
stochastic computations. The focus is on efficient high-order methods suitable for practical …
Time capsule for geotechnical risk and reliability
This paper is motivated by the Time Capsule Project (TCP) of the International Society for
Soil Mechanics and Geotechnical Engineering (ISSMGE). The historical developments of …
Soil Mechanics and Geotechnical Engineering (ISSMGE). The historical developments of …
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification
State-of-the-art computer codes for simulating real physical systems are often characterized
by vast number of input parameters. Performing uncertainty quantification (UQ) tasks with …
by vast number of input parameters. Performing uncertainty quantification (UQ) tasks with …
The random feature model for input-output maps between banach spaces
Well known to the machine learning community, the random feature model is a parametric
approximation to kernel interpolation or regression methods. It is typically used to …
approximation to kernel interpolation or regression methods. It is typically used to …
Recent trends in the modeling and quantification of non-probabilistic uncertainty
This paper gives an overview of recent advances in the field of non-probabilistic uncertainty
quantification. Both techniques for the forward propagation and inverse quantification of …
quantification. Both techniques for the forward propagation and inverse quantification of …
Inverse problems: a Bayesian perspective
The subject of inverse problems in differential equations is of enormous practical
importance, and has also generated substantial mathematical and computational …
importance, and has also generated substantial mathematical and computational …
A GF-discrepancy for point selection in stochastic seismic response analysis of structures with uncertain parameters
In the stochastic dynamic analysis of nonlinear structures, the strategy of point selection
plays a critical role in achieving the tradeoffs between the accuracy and efficiency. To this …
plays a critical role in achieving the tradeoffs between the accuracy and efficiency. To this …
[کتاب][B] Stochastic dynamics of structures
In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and
techniques for stochastic dynamics analysis, prediction of reliability, and system control of …
techniques for stochastic dynamics analysis, prediction of reliability, and system control of …
Optimal discretization of random fields
A new method for efficient discretization of random fields (ie, their representation in terms of
random variables) is introduced. The efficiency of the discretization is measured by the …
random variables) is introduced. The efficiency of the discretization is measured by the …
A univariate dimension-reduction method for multi-dimensional integration in stochastic mechanics
This paper presents a new, univariate dimension-reduction method for calculating statistical
moments of response of mechanical systems subject to uncertainties in loads, material …
moments of response of mechanical systems subject to uncertainties in loads, material …