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Data-driven non-intrusive reduced order modelling of selective laser melting additive manufacturing process using proper orthogonal decomposition and convolutional autoencoder
Published 2025-08-01“…The comparison of statistical moments from high-fidelity simulation results with ROM predictions reveals a strong correlation. …”
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Sparse sufficient dimension reduction for directional regression
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Noisier2Inverse: Self-Supervised Learning for Image Reconstruction With Correlated Noise
Published 2025-01-01“…Our approach learns a reconstruction function without requiring ground truth data and is applicable in settings where measurement noise is statistically correlated. …”
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THE EFFECTIVENESS OF VALIDATION MEASUREMENTS IN AUTOMATED SYSTEMS OF THE POWER SUPPLY SYSTEMS CONTROL IN ACCORDANCE WITH LIMIT VALUES
Published 2017-09-01“…With this regard, the objective of a reasonable narrowing of the range of valid values of the variables, that uses the theory of statistical decisions, acquires high relevance.…”
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Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations
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Snow cover setting-up dates in the north of Eurasia: relations and feedback to the macro-scale atmospheric circulation
Published 2015-03-01“…Variations of snow cover onset data in 1950–2008 based on daily snow depth data collected at first-order meteorological stations of the former USSR compiled at the Russia Institute of Hydrometeorological Information are analyzed in order to reveal climatic norms, relations with macro-scale atmospheric circulation and influence of snow cover anomalies on strengthening/weakening of westerly basing on observational data and results of simulation using model Planet Simulator, as well. …”
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Local Influence Analysis for Quasi-Likelihood Nonlinear Models with Random Effects
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Model and Variable Selection Procedures for Semiparametric Time Series Regression
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CUR matrix approximation through convex optimization for feature selection
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Liu Estimation Method in the Zero-Inflated Conway Maxwell Poisson Regression Model
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Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients☆
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Assessing By Model Fitting Criteria and Comparing Between Stirling and Aitken Interpolation Formulas to Determine the Preferred Treatment of Choice, (Surgery) Or (Surgery with Chem...
Published 2024-06-01“… Numerical analysis is a branch of mathematical science; Interpolation is a method in Numerical analysis used for creating a model for group of discrete data points. …”
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Modern techniques in variance estimation with auxiliary information: a logarithmic perspective
Published 2025-12-01“…Variance estimation is essential to statistical analysis because it sheds light on the accuracy and dependability of estimations. …”
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Reliability Estimation for the Gull Alpha Power Pareto Model Under Progressive Type-I Censoring
Published 2025-01-01“…Interval estimation was also addressed using two approaches: asymptotic confidence intervals based on MLE, and highest posterior density intervals in the Bayesian framework. A numerical study of the GAPP model under PCS-TI was performed using Monte Carlo simulations and real-world data related to the failure times of an airplane’s air conditioning system. …”
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The big gap: perceived, experienced and reported discrimination among immigrants in Italy
Published 2017-12-01“…The article will present a comparison between the num-ber and trends of complaints received by the Italian Equality body against discrimination during ten years, and data from a national inquiry of the Italian Institute of Statistics de-tecting the experiences of discrimination suffered by foreign nationals resident in Italy. …”
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