d-Variate Boolean interpolation

TL;DR: The error bounds show that the polynomial interpolation on a d-dimensional cube, where d is large, is universal, i.e., almost optimal for many different function spaces.

TL;DR: An overview of solution and estimation techniques for dynamic stochastic general equilibrium models and the foundations of numerical approximation techniques as well as statistical inference are covered.

TL;DR: The case is made for quantum machine learning: An inductive molecular modeling approach which can be applied to quantum chemistry problems.

TL;DR: This paper developed a projection algorithm to approximate equilibria in overlapping generations economies with a large number of generations and stochastic aggregate production, where the state space includes the distribution of wealth across generations.

TL;DR: The notion of a “transfinite element” is introduced which, in brief, is an invertible mapping from a square parameter domainJ onto a closed, bounded and simply connected regionℛ in thexy-plane together with a ‘transFinite’ blending-function type interpolant to the dependent variablef defined overℚ.

TL;DR: A general theory to encompass this case has been proposed in this article, and a full report on this subject is in preparation and will appear among the publications of the Center for Numerical Analysis, University of Texas.