In an extension to some previous work on the topic, we show how all classical polynomial-based quadrature rules can be interpreted as Bayesian quadrature rules if the covariance kernel is selected suitably. As the resulting Bayesian quadrature rules have zero posterior integral variance, the results of this article are mostly of theoretical interest in clarifying the relationship between the two different approaches to numerical integration.Peer reviewe
Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the...
Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical ...
Diese Arbeit befasst sich mit Gaußschen Quadraturformeln und der Auswertung einer speziellen Familie...
In an extension to some previous work on the topic, we show how all classical polynomial-based quadr...
This article is concerned with Gaussian process quadratures, which are numerical integration methods...
AbstractPhysicists know how to integrate over all possible paths, computer-vision experts want to as...
Abstract—This paper is concerned with the use of Gaussian process regression based quadrature rules ...
This paper is concerned with the use of Gaussian process regression based quadrature rules in the co...
We construct and analyze generalized Gaussian quadrature rules for integrands with endpoint singular...
NOT REPRODUCE LEGIBLY. Generalized Gaussian quadratures appear to have been introduced by Markov [11...
To compute integrals on bounded or unbounded intervals we propose a new numerical approach by using ...
© 2020 Walter de Gruyter GmbH, Berlin/Boston. We motive and calculate Newton-Cotes quadrature integr...
Integration is a frequently used operator in mathematical models of economic systems. When these int...
AbstractThe theory of strong moment problems has provided Gaussian quadrature rules for approximate ...
In this paper a construction of a one-parameter family of quadrature formulas is presented. This fam...
Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the...
Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical ...
Diese Arbeit befasst sich mit Gaußschen Quadraturformeln und der Auswertung einer speziellen Familie...
In an extension to some previous work on the topic, we show how all classical polynomial-based quadr...
This article is concerned with Gaussian process quadratures, which are numerical integration methods...
AbstractPhysicists know how to integrate over all possible paths, computer-vision experts want to as...
Abstract—This paper is concerned with the use of Gaussian process regression based quadrature rules ...
This paper is concerned with the use of Gaussian process regression based quadrature rules in the co...
We construct and analyze generalized Gaussian quadrature rules for integrands with endpoint singular...
NOT REPRODUCE LEGIBLY. Generalized Gaussian quadratures appear to have been introduced by Markov [11...
To compute integrals on bounded or unbounded intervals we propose a new numerical approach by using ...
© 2020 Walter de Gruyter GmbH, Berlin/Boston. We motive and calculate Newton-Cotes quadrature integr...
Integration is a frequently used operator in mathematical models of economic systems. When these int...
AbstractThe theory of strong moment problems has provided Gaussian quadrature rules for approximate ...
In this paper a construction of a one-parameter family of quadrature formulas is presented. This fam...
Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on the...
Two conceptual developments in the Bayesian automatic adaptive quadrature approach to the numerical ...
Diese Arbeit befasst sich mit Gaußschen Quadraturformeln und der Auswertung einer speziellen Familie...