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Estimating uncertainty of machine learning models is essential to assess the quality of the predictions that these models provide. However, there are several factors that influence the quality of uncertainty estimates, one of which is the…

Machine Learning · Computer Science 2022-11-03 Yuko Kato , David M. J. Tax , Marco Loog

The issue of asymmetric uncertainties resulting from fits, nonlinear propagation and systematic effects is reviewed. It is shown that, in all cases, whenever a published result is given with asymmetric uncertainties, the value of the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 G. D'Agostini

This paper presents a detailed analysis of uncertainty matrices (i.e. measurement covariance matrices) associated with multiple complex-valued microwave scattering S-parameter measurements. The analysis is based on forming combinations of…

Instrumentation and Detectors · Physics 2018-09-20 Nick M. Ridler , Martin J. Salter

The Guide to the Expression of Uncertainty in Measurement advocates the use of an 'effective number of degrees of freedom' for the calculation of an interval of measurement uncertainty. However, it does not describe how this number is to be…

Data Analysis, Statistics and Probability · Physics 2013-11-05 R. Willink , B. D. Hall

The limits of reversible deformation in graphene under various loadings are examined using lattice-dynamical stability analysis. This information is then used to construct a comprehensive lattice-stability limit surface for graphene, which…

Materials Science · Physics 2015-09-21 Sandeep Kumar , David Parks

Uncertainty quantification by ensemble learning is explored in terms of an application from computational optical form measurements. The application requires to solve a large-scale, nonlinear inverse problem. Ensemble learning is used to…

Machine Learning · Computer Science 2021-03-03 Lara Hoffmann , Ines Fortmeier , Clemens Elster

Educators must make decisions about learner expectations and skills on which to focus when it comes to laboratory activities. There are various approaches but the general pattern is to encourage students to measure ordered pairs, plot a…

Physics Education · Physics 2023-03-30 Kevin L. Haglin

Despite ongoing research, testing the flatness of discrete-time systems remains a challenging problem. To date, only the property of forward-flatness - a special case of difference-flatness - can be checked in a computationally efficient…

Optimization and Control · Mathematics 2026-02-10 Johannes Schrotshamer , Bernd Kolar , Markus Schöberl

We study algebraicity and smoothness of fixed point stacks for flat group schemes which have a finite composition series whose factors are either reductive or proper, flat, finitely presented, acting on algebraic stacks with affine,…

Algebraic Geometry · Mathematics 2022-09-19 Matthieu Romagny

A novel multi-scale finite element formulation for contact mechanics between nominally smooth but microscopically rough surfaces is herein proposed. The approach integrates the interface finite element method (FEM) for modelling interface…

Computational Engineering, Finance, and Science · Computer Science 2025-04-03 Jacopo Bonari , Maria R. Marulli , Nora Hagmeyer , Matthias Mayr , Alexander Popp , Marco Paggi

This paper investigates the geometric inverse problem of recovering the bottom shape from surface measurements of water waves. Using the general water-waves system on a bounded subdomain of the fluid domain, we address this inverse problem,…

Analysis of PDEs · Mathematics 2026-04-08 Noureddine Lamsahel , Lionel Rosier

Measurement uncertainty plays a critical role in the process of experimental physics. It is useful to be able to assess student proficiency around the topic to iteratively improve instruction and student learning. For the topic of…

Physics Education · Physics 2023-08-23 Gayle Geschwind , Michael Vignal , H. J. Lewandowski

Uncertainty relations give upper bounds on the accuracy by which the outcomes of two incompatible measurements can be predicted. While established uncertainty relations apply to cases where the predictions are based on purely classical data…

Quantum Physics · Physics 2012-10-18 Marco Tomamichel , Renato Renner

Model analysis provides a mechanism for representing student learning as measured by standard multiple-choice surveys. The model plot contains information regarding both how likely students in a particular class are to choose the correct…

Physics Education · Physics 2016-10-12 Trevor I. Smith

The concept of quantum coherence, including various ways to quantify the degree of coherence with respect to the prescribed basis, is currently the subject of active research. The complementarity of quantum coherence in different bases was…

Quantum Physics · Physics 2017-09-08 Alexey E. Rastegin

Modern autonomous systems with machine learning components often use uncertainty quantification to help produce assurances about system operation. However, there is a lack of consensus in the community on what uncertainty is and how to…

Systems and Control · Electrical Eng. & Systems 2026-01-27 Sampada Deglurkar , Haotian Shen , Anish Muthali , Marco Pavone , Dragos Margineantu , Peter Karkus , Boris Ivanovic , Claire J. Tomlin

This paper describes, in detail, techniques for measuring the Hurst parameter. Measurements are given on artificial data both in a raw form and corrupted in various ways to check the robustness of the tools in question. Measurements are…

Statistics Theory · Mathematics 2007-06-13 Richard G. Clegg

We classify all smooth flat Riemannian metrics on the two-dimensional plane. In the complete case, it is well-known that these metrics are isometric to the Euclidean metric. In the incomplete case, there is an abundance of…

Differential Geometry · Mathematics 2020-01-14 Vincent E. Coll, , Lee B. Whitt

The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is…

We determine the variance for the fluctuations of the arithmetic measures obtained by collecting all closed geodesics on the modular surface with the same discriminant and ordering them by the latter. This arithmetic variance differs by…

Number Theory · Mathematics 2009-04-15 Wenzhi Luo , Zeev Rudnick , Peter Sarnak