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We propose a coefficient that measures the dependence among large values for spatial processes of maxima. Its main properties are: a) $k$ locations can be taken into account; b) it takes values in $[0,1]$ and higher values indicate stronger…

Statistics Theory · Mathematics 2015-06-22 Helena Ferreira , Luisa Pereira

A unified construction of high order shape functions is given for all four classical energy spaces ($H^1$, $H(\mathrm{curl})$, $H(\mathrm{div})$ and $L^2$) and for elements of "all" shapes (segment, quadrilateral, triangle, hexahedron,…

Numerical Analysis · Mathematics 2016-05-31 Federico Fuentes , Brendan Keith , Leszek Demkowicz , Sriram Nagaraj

In this work we study the Wigner functions, which are the quantum analogues of the classical phase space density, and show how a full rigorous semiclassical scheme for all orders of \hbar can be constructed for them without referring to the…

Chaotic Dynamics · Physics 2009-11-07 Gregor Veble , Marko Robnik , Valery Romanovski

Highly concentrated functions play an important role in many research fields including control system analysis and physics, and they turned out to be the key idea behind inverse Laplace transform methods as well. This paper uses the…

Performance · Computer Science 2019-01-28 Gabor Horvath , Illes Horvath , Miklos Telek

We propose a new approach for controlling the characteristics of certain mesh faces during optimization of high-order curved meshes. The practical goals are tangential relaxation along initially aligned curved boundaries and internal…

Numerical Analysis · Mathematics 2021-05-27 Patrick Knupp , Tzanio Kolev , Ketan Mittal , Vladimir Z. Tomov

The reduction algorithms for functional determinants of differential operators on spacetime manifolds of different topological types are presented, which were recently used for the calculation of the no-boundary wavefunction and the…

General Relativity and Quantum Cosmology · Physics 2009-10-22 A. O. Barvinsky

Higher-order probabilistic programming languages allow programmers to write sophisticated models in machine learning and statistics in a succinct and structured way, but step outside the standard measure-theoretic formalization of…

Programming Languages · Computer Science 2020-12-03 Chris Heunen , Ohad Kammar , Sam Staton , Hongseok Yang

How can we explain the predictions of a black-box model? In this paper, we use influence functions -- a classic technique from robust statistics -- to trace a model's prediction through the learning algorithm and back to its training data,…

Machine Learning · Statistics 2021-01-01 Pang Wei Koh , Percy Liang

Adaptive estimation of linear functionals over a collection of parameter spaces is considered. A between-class modulus of continuity, a geometric quantity, is shown to be instrumental in characterizing the degree of adaptability over two…

Statistics Theory · Mathematics 2007-06-13 T. Tony Cai , Mark G. Low

Sub-sampling is a common and often effective method to deal with the computational challenges of large datasets. However, for most statistical models, there is no well-motivated approach for drawing a non-uniform subsample. We show that the…

Machine Learning · Statistics 2017-09-07 Daniel Ting , Eric Brochu

The paper studies generalized differentiability properties of the marginal function of parametric optimal control problems of semilinear elliptic partial differential equations. We establish upper estimates for the regular and the limiting…

Optimization and Control · Mathematics 2018-07-17 Nguyen Thanh Qui , Daniel Wachsmuth

We consider Lorentzian CFT Wightman functions in momentum space. In particular, we derive a set of reference formulas for computing two- and three-point functions, restricting our attention to three-point functions where the middle operator…

High Energy Physics - Theory · Physics 2020-12-08 Nikhil Anand , Zuhair U. Khandker , Matthew T. Walters

In this paper, we investigate the relationship between the Hilbert functions and the associated properties of the graded modules. To attain this, we construct the graded modules from the sets of points in projective space, $\mathbb{P}_k^n$…

Commutative Algebra · Mathematics 2023-04-11 Damas Karmel Mgani , Makungu Mwanzalima

Parameter-dependent models arise in many contexts such as uncertainty quantification, sensitivity analysis, inverse problems or optimization. Parametric or uncertainty analyses usually require the evaluation of an output of a model for many…

Numerical Analysis · Mathematics 2018-10-22 Anthony Nouy

This article is meant as a gentle introduction to the "topological terms" that often play a decisive role in effective theories describing topological quantum effects in condensed matter systems. We first take up several prominent examples,…

Strongly Correlated Electrons · Physics 2015-02-20 Akihiro Tanaka , Shintaro Takayoshi

The new notion of operator/matrix $k$-tone functions is introduced, which is a higher order extension of operator/matrix monotone and convex functions. Differential properties of matrix $k$-tone functions are shown. Characterizations,…

Functional Analysis · Mathematics 2014-05-19 Uwe Franz , Fumio Hiai , Éric Ricard

Systematic expansion schemes in functional approaches require the inclusion of higher order vertices. These vertices are expanded in independent tensor bases with a rapidly increasing number of basis elements. Amongst the related tasks are…

High Energy Physics - Theory · Physics 2025-03-10 Jens Braun , Andreas Geißel , Jan M. Pawlowski , Franz R. Sattler , Nicolas Wink

In this article, we construct semiparametrically efficient estimators of linear functionals of a probability measure in the presence of side information using an easy empirical likelihood approach. We use estimated constraint functions and…

Methodology · Statistics 2023-03-01 Shan Wang , Hanxiang Peng

We give sufficient conditions under which solutions of finite-difference schemes in the space variable for second order possibly degenerate parabolic and elliptic equations admit estimates of spatial derivatives up to any given order…

Numerical Analysis · Mathematics 2008-05-21 István Gyöngy , Nicolai Krylov

The pseudospherical functions on one-sheet, two-dimensional hyperboloid are discussed. The simplest method of construction of these functions is introduced using the Fock space structure of the representation space of the su(1,1) algebra.…

Mathematical Physics · Physics 2015-05-27 K. Kowalski , J. Rembielinski , A. Szczesniak
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