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Here, I review facts that are most probably known, namely that the information gain criterion used to drive experimental design in a linear-Gaussian model is submodular, so that a well-known approximation guarantee holds for the sequential greedy algorithm ...
We investigate how nonlinearity and topological disorder affect the energy relaxation of local kicks in coarse-grained network models of proteins. We find that nonlinearity promotes long-range, coherent transfer of substantial energy to specific functional ...
We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. The identified Volterra kernels reveal the spectro-temporal patterns that are l ...
Understanding the long-term seasonal dynamics of alpine glacierized basins is essential to evaluating their relation to climatic forcing. We focus on process knowledge by following a minimalist approach, and propose a spatially lumped nonlinear differentia ...
In this work we consider the Reduced Basis method for the solution of parametrized advection-reaction partial differential equations. For the generation of the basis we adopt a stabilized finite element method and we define the Reduced Basis method in the ...
We present a framework to apply Volterra series to analyze multilayered perceptrons trained to estimate the posterior probabilities of phonemes in automatic speech recognition. The identified Volterra kernels reveal the spectro-temporal patterns that are l ...
Parameter identification of microscopic driving models is a difficult task. This is caused by the fact that parameters-such as reaction time, sensitivity to stimuli, etc.-are generally not directly observable from common traffic data, but also due to the l ...
A novel approach is presented for the identification of constitutive parameters of linear poroelastic materials from indentation tests. Load-controlled spherical indentation with a ramp-hold creep profile is considered. The identification approach is based ...
We analyze a simple hierarchical architecture consisting of two multilayer perceptron (MLP) classifiers in tandem to estimate the phonetic class conditional probabilities. In this hierarchical setup, the first MLP classifier is trained using standard acous ...
This paper presents a numerical procedure of material parameter identification for the coupled hydromechanical boundary value problem (BVP) of the self-boring pressuremeter test (SBPT) in clay. First, the neural network (NN) technique is applied to obtain ...
