Multivariate Approximation and Interpolation with Applications – MAIA
September 19 – 23, 2016
Approximation theory has evolved from classical work by Chebyshev, Weierstrass and Bernstein into an area that combines a deep theoretical analysis of approximation with insights leading to the invention of new computational techniques. Such invaluable tools of modern computation as orthogonal polynomials, splines, finite elements, Bézier curves, NURBS, radial basis functions, wavelets and subdivision surfaces have been developed and analysed with the prominent help of ideas coming from approximation theory.
The workshop is devoted to the approximation of functions of two or more variables. This area has many challenging open questions and its wide variety of applications includes problems of computer aided design, mathematical modelling, data interpolation and fitting, signal analysis and image processing. The Workshop will be the 13th Conference of MAIA series. This conference is intended to be a platform for researchers in approximation theory and its applications with a strong interest in multivariate approximation and interpolation. The aim of this workshop is also to bring together researchers working in these topics. Participants will present and discuss their latest results. Relevant topics of the MAIA conference include, but are not limited to the following:

Scientific Committee
Carl de Boor (University of Wisconsin) Organizing Committee Abderrahman Bouhamidi (Université Littoral Côte d’Opale Calais) Speakers
Bspline finite element method for dynamic deflection of beam deformation model
Rational Geometric Splines: construction and applications in the representation of smooth surfaces
Some Bivariate Generalizations of Berrut’s Rational Interpolants
Some applications of the wavelet transform with signaldependent dilation factor
Multigrid and subdivision
The unitary extension principle and its generalizations
Error bounds for conditionally positive definite kernels without polynomial terms
On the rescaled method for RBF approximation
Deep learning on Manifolds
A unified interpolatory subdivision scheme for quadrilateral meshes
Reconstruction of 2D shapes and 3D objects from their 1D parallel crosssections by « geometric piecewise linear interpolation
Partially Nested Hierarchical BSplines
Estimation of linear integral operator from scattered impulse reponses
Some Recent Insights into Computing with Positive Definite Kernels
Directional timefrequency analysis via continuous frames
Sampling for solutions of the heat equation
Stable Phase Retrieval in Infinite Dimensions
A moment matrix approach to computing symmetric cubatures
On Computing the Derivative of the Lebesgue Function of Barycentric Rational Interpolation
Interpolatory and noninterpolatory Hermite subdivision schemes reproducing polynomials
Low Rank Spline Surfaces
25+ Years of Wavelets for PDEs
Error estimates for multilevel Gaussian quasiinterpolation on the torus
Simplex spline bases on the PowellSabin 12 split
Spline spaces over planar Tmeshes and Extended complete Tchebycheff spaces
BSplines and Clifford Algebra
Smoothing of vector and Hermite
Sparse multivariate polynomialexponential representation and interpolation
Dictionary data assimilation for recovery problems
Recent Progress on RAGS
Adaptive hierarchical lowrank approximation of multivariate functions using statistical methods
Recent advances on Accuracy and Stability in Approximation and C.A.G.D.
HelmholtzHodge decomposition, Divergencefree wavelets and applications
Less is enough: localizing neural sources by the random sampling method
Sparse approximation by modified Prony method
Spherical Splines
Applications of subdivision schemes to combinatorics and to number theory
Variational Bézier or Bspline curves and surfaces
Approximation and Modeling with Ambient BSplines
Convergence of corner cutting algorithms refining points and nets of functions
Applications of variably scaled kernels
Nonsymmetric kernelbased greedy approximation
Prony’s problem and superresolution in several variables: structure and algorithms
Adaption of tensor product spline spaces to approximation on domains
Local approximation methods using hierarchical splines
Methods for constructing multivariate tight wavelet frames
Multigrid and Subdivision: grid transfer operators
Irregular Tight Wavelet Frames: Matrix Approach
Anisotropic Diagonal Scaling Matrices and Subdivision Schemes in Dimension d
Kernelbased Discretisation for Solving Matrixvalued PDEs
Sixthorder Weighted essentially nonoscillatory schemes based on exponential polynomials
Univariate Nonlinear Approximation Scheme for Piecewise Smooth functions 