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Many quantitative genetic statistics are functions of variance components, for which a large number of replicates is needed for precise estimates and reliable measures of uncertainty, on which sound interpretation depends. Moreover, in large experiments th ...
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation propagation algorithm, we are able to approximate the full poster ...
Evaluating biometric authentication performance is a complex task because the performance depends on the user set size, composition and the choice of samples. We propose to reduce the performance dependency of these three factors by deriving appropriate co ...
In the last decade, several Life Cycle Assessment (LCA) methods for assessing impact of products on living resources have been developed. Beyond the quantified assessments of impacts on living systems, it also checked the feasibility of the impact assessme ...
This paper describe an application of a transductive method for risk mapping which allows to compute the confidence interval of an estimation, without any assumption on data distribution, except identity and independancy of inputs. The method is compared t ...
In this paper, we propose a new posterior based scoring approach for keyword and non keyword (garbage) elements. The estimation of these scores is based on HMM state posterior probability definition, taking into account long contextual information and the ...
In this paper, we propose a new posterior based scoring approach for keyword and non keyword (garbage) elements. The estimation of these scores is based on HMM state posterior probability definition, taking into account long contextual information and the ...
In this paper, the design of probabilistic observers for mass-balance based bio- process models is investigated. It is assumed that the probability density function of every uncertain parameter, input and/or initial state is known a priori. Then, the proba ...
In this paper, probabilistic observers are considered for a class of continuous biological processes described by mass-balance-based models. It is assumed that the probability density functions (PDFs) of the uncertain parameters and inputs of the model, as ...
The performance of many color science and imaging algorithms are evaluated based on their mean errors. However, if these errors are not normally distributed, statistical evaluations based on the mean are not appropriate performance metrics. We present a no ...