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Titlebook: Conformal and Probabilistic Prediction with Applications; 5th International Sy Alexander Gammerman,Zhiyuan Luo,Vladimir Vovk Conference pro

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Hidden Markov Models with Confidenceur attention is focused to applications that require a list of potential sequences as a prediction. We propose a novel method based on Conformal Prediction (CP) that, for an arbitrary confidence level ., produces a list of candidate sequences that contains the correct sequence of hidden states with
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Effective Design for Sobol Indices Estimation Based on Polynomial Chaos Expansionstput of the analyzed mathematical model. We consider a problem of selection of experimental design points for Sobol’ indices estimation. Based on the concept of .-optimality, we propose a method for constructing an adaptive design of experiments, effective for the calculation of Sobol’ indices from
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Extended Regression on Manifolds Estimationality q < p embedded in an ambient high-dimensional space R., to m-dimensional outputs. Regression on manifold problem is to estimate a triple (f(X), J.(X), .), which includes Jacobian J. of the mapping f, from given sample consisting of ‘input-output’ pairs. If some mapping h transforms Input manif
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Conformal Prediction of Disruptions from Scratch: Application to an ITER Scenarioess rate (rate of disruptions predicted correctly) increases and the false alarm rate (rate of non-disruptive discharges misclassified) decreases, using conformal prediction (CP) rather than conventional methodology from scratch. CP from scratch achieves a success rate of . with the first model and only one disruptive discharge.
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