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Multivariate approximation and interpolation
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A multi-scale framework for BOD<sub>5</sub> prediction from water quality to hydro-geomorphic interpolation. [PDF]
Arzhangi A, Partani S.
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DynamicSeq2SeqXGB for PM2.5 imputation in extremely sparse environmental monitoring networks. [PDF]
Safarov R +5 more
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The Subgaleal Pocket Approach for Cochlear Implant Surgery
The Laryngoscope, EarlyView.
Nihar Rama +5 more
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A comprehensive analysis of perturbation methods in explainable AI feature attribution validation for neural time series classifiers. [PDF]
Šimić I, Veas E, Sabol V.
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Multivariate Perpendicular Interpolation
SIAM Journal on Numerical Analysis, 1985One of the really important problems of multivariate approximation theory is the one of interpolating to a large number of scattered data. Applications include the modeling of physical phenomena involving space and time coordinates and the computer aided design (CAD) of geometric objects.
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Multivariate rational interpolation
Computing, 1985The problem of approximating a multivariate function by interpolatory functions is not an easy one. Many papers have already been published on the subject of polynomial interpolation and also on the subject of multivariate Padé approximation. But the problem of multivariate rational interpolation has only recently been considered.
Cuyt, Annie A.M., Verdonk, B.M.
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Multivariable Curve Interpolation
Journal of the ACM, 1964The problem of defining a smooth surface through an array of points in space is well known. Several methods of solution have been proposed. Generally, these restrict the set of points to be one-to-one defined over a planar rectangular grid ( X , Y -plane).
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