We begin by introducing the main ideas of the paper, and we give a brief description of the method proposed. Next, we discuss an alternative approach based on B-spline expansion, and lastly we make some comments on the method’s convergence rate.Analysis and Stochastic
© 2017 Author(s). This paper develops meshless methods for probabilistically describing discretisati...
The interpretation of numerical methods, such as finite difference methods for differential equation...
peer reviewedDifferential equations (DEs) are commonly used to describe dynamic sys- tems evolving ...
We begin by introducing the main ideas of the paper, and we give a brief description of the method p...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
This paper advocates expansion of the role of Bayesian statistical inference when formally quantifyi...
We explore probability modelling of discretization uncertainty for system states defined implicitly ...
We explore probability modelling of discretization uncertainty for system states defined implicitly ...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
We commend the authors for an exciting paper which provides a strong contribution to the emerging fi...
The numerical solution of differential equations can be formulated as an inference problem to which ...
We commend the authors for an exciting paper which provides a strong contribution to the emerging fi...
Numerical analysis is the branch of mathematics that studies algorithms that compute approximations ...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
A recently introduced class of probabilistic (uncertainty-aware) solvers for ordinary differential e...
© 2017 Author(s). This paper develops meshless methods for probabilistically describing discretisati...
The interpretation of numerical methods, such as finite difference methods for differential equation...
peer reviewedDifferential equations (DEs) are commonly used to describe dynamic sys- tems evolving ...
We begin by introducing the main ideas of the paper, and we give a brief description of the method p...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
This paper advocates expansion of the role of Bayesian statistical inference when formally quantifyi...
We explore probability modelling of discretization uncertainty for system states defined implicitly ...
We explore probability modelling of discretization uncertainty for system states defined implicitly ...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
We commend the authors for an exciting paper which provides a strong contribution to the emerging fi...
The numerical solution of differential equations can be formulated as an inference problem to which ...
We commend the authors for an exciting paper which provides a strong contribution to the emerging fi...
Numerical analysis is the branch of mathematics that studies algorithms that compute approximations ...
In this paper, we present a formal quantification of uncertainty induced by numerical solutions of o...
A recently introduced class of probabilistic (uncertainty-aware) solvers for ordinary differential e...
© 2017 Author(s). This paper develops meshless methods for probabilistically describing discretisati...
The interpretation of numerical methods, such as finite difference methods for differential equation...
peer reviewedDifferential equations (DEs) are commonly used to describe dynamic sys- tems evolving ...
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