... simulator **for** a limited number of inputs called the Design of Experiments ...as **Gaussian** **Process** **modeling** ...of **Gaussian** Processes ...distributions **for** the response values at any ...

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... framework **for** the spatio-temporal analysis of large-scale collections of multi-modal brain ...accounting **for** the uncertainty of the temporal profiles and brain structures we wish to ...trajectory ...

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... time. **For** example, the creation of functional surfaces from the constraints of the specifi- cations, the generation of the assembly of these surfaces and the verification of volumes of work could be done by the ...

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... Our contributions on group **kernels** are now listed. We exploit the hierarchy group/level by revisiting a nested Bayesian linear model where the response term is a sum of a group effect and a level effect. The level ...

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... 3.2. **Additive** manufacturing and environment : state of the art In **additive** manufacturing, parts are obtained with a successive addition of ...deposition **modeling** machines based on Eco-Indicator 95 ...

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... new **kernels** from old with KANOVA While kernel methods and **Gaussian** **process** modelling have proven efficient in a number of classification and prediction problems, finding a suitable kernel **for** ...

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... algorithm **for** the automatic knot insertion using an evolution criterion based on the maximisation of the integrated squared error of the MAP ...considered **additive** (and block-**additive**) ...considering ...

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... However, **for** its application to complex industrial problems, developing a robust implementation methodology is ...the **Gaussian** **process** ...and **for** small size samples (a few ...

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... tested **for** the inference of mRNA ...is. **For** further discussions, we refer to GP-mRNA and GP-Protein to the physically- inspired GP with prior over the mRNA or protein concentrations, ...

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... obtain **Gaussian** processes indexed by probability ...results **for** these ...studied **kernels**, compared to more standard **kernels** operating on finite dimensional projections of the ...the ...

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... and **Gaussian** **process** modelling have proven efficient in a number of classification and prediction problems, finding a suitable kernel **for** a given application is often judged ...stationary ...

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... However, **for** large-scale prob- lems, the full sequential **process** can prove prohibitively costly in terms of ...methods **for** symmetric definite positive linear systems, such as the conjugate gradient ...

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... holds **for** the same stability index members, in general the **additive** convolution of the impulsive stable interference and lighter tailed **Gaussian** thermal noise will not result in a stable ...Inverse ...

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... which **Gaussian** **process** regression is one of the most popular ...framework **for** incorporating any type of linear constraints in **Gaussian** **process** **modeling**, including common bound ...

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... to **Gaussian** **Process** Regression **for** creating probabilistic models from few replicated specimens displaying a heteroscedastic ...model **for** the permeability in order to quantify the effectiveness ...

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... 2 **Modeling** Left-Looking and Right-Looking Computations We consider a distributed-memory dense partial factorization relying on a dyna- mic asynchronous pipelined ...allow **for** efficient pivot searches ...

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... used **for** all the methods are also detailed. As far as the evaluation **process** is concerned, the Structural Similarity Index Measure (SSIM) [21] is reported and plotted as a function of the number of ...

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... derived **for** regression and classification with support vector machines, they include classical techniques such as least-squares methods and extend them to nonlinear functional ...the **Gaussian** kernel κ (x i ...

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... (simply **Gaussian**) as a function of the prior parameterization on the Student-t degrees of freedom parameter, which they took to be ν ∼ Exp(θ = ...framework **for** studying sensitivity to this ...“essentially ...

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... 0 **for** some nominal values of its parameters, more or less big fluctuations around these nominal values can occur — due to environmental conditions **for** instance — and induce deviations of kθk around 0, where ...

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