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This letter explores how a reinterpretation of the generalized uncertainty principle as an effective variation of Planck's constant provides a physical explanation for a number of fundamental quantities and couplings. In this context, a…

General Physics · Physics 2024-09-02 Ahmed Farag Ali , Jonas Mureika , Elias C. Vagenas , Ibrahim Elmashad

Non-probabilistic convex model utilizes a convex set to quantify the uncertainty domain of uncertain-but-bounded parameters, which is very effective for structural uncertainty analysis with limited or poor-quality experimental data. To…

Other Statistics · Statistics 2018-01-18 Ni Bingyu , Jiang Chao , Huang Zhiliang

The article focuses on determining the predictive uncertainty of a model on the example of atrial fibrillation detection problem by a single-lead ECG signal. To this end, the model predicts parameters of the beta distribution over class…

Computer Vision and Pattern Recognition · Computer Science 2018-08-08 Alexander Kuvaev , Roman Khudorozhkov

Bayesian model comparison (BMC) offers a principled probabilistic approach to study and rank competing models. In standard BMC, we construct a discrete probability distribution over the set of possible models, conditional on the observed…

Machine Learning · Statistics 2023-02-22 Marvin Schmitt , Stefan T. Radev , Paul-Christian Bürkner

The Planck constant ($\hbar$) plays a pivotal role in quantum physics. Historically, it has been proposed as postulate, part of a genius empirical relationship $E=\hbar \omega$ in order to explain the intensity spectrum of the blackbody…

Optics · Physics 2015-05-04 Real Tremblay , Nicolas Doyon , Claudine Ni Allen

From positions, attained by modern theoretical physics in understanding of the universe bases, the methodological and philosophical analysis of fundamental physical concepts and their formal and informal connections with the real economic…

General Physics · Physics 2015-03-13 Vladimir Soloviev , Vladimir Saptsin

In order to trust the predictions of a machine learning algorithm, it is necessary to understand the factors that contribute to those predictions. In the case of probabilistic and uncertainty-aware models, it is necessary to understand not…

Machine Learning · Statistics 2024-08-19 Danny Wood , Theodore Papamarkou , Matt Benatan , Richard Allmendinger

Covariance matrix estimation and principal component analysis (PCA) are two cornerstones of multivariate analysis. Classic textbook solutions perform poorly when the dimension of the data is of a magnitude similar to the sample size, or…

Statistics Theory · Mathematics 2014-06-25 Olivier Ledoit , Michael Wolf

In the present work we suggest a non-local generalization of quantum theory which include quantum theory as a particular case. On the basis of the idea, that Planck constant is an adiabatic invariant of the free/coupled electromagnetic…

General Physics · Physics 2016-04-15 A. Lipovka

Statistical uncertainty of different filtration techniques for market network analysis is studied. Two measures of statistical uncertainty are discussed. One is based on conditional risk for multiple decision statistical procedures and…

Statistical Finance · Quantitative Finance 2015-06-17 V. A. Kalyagin , A. P. Koldanov , P. A. Koldanov , P. M. Pardalos , V. A. Zamaraev

Motivated by the Dirac idea that fundamental constant are dynamical variables and by conjectures on quantum structure of spacetime at small distances, we consider the possibility that Planck constant $\hbar$ is a time depending quantity,…

Quantum Physics · Physics 2015-12-16 Gianpiero Mangano , Fedele Lizzi , Alberto Porzio

In computational materials science, mechanical properties are typically extracted from simulations by means of analysis routines that seek to mimic their experimental counterparts. However, simulated data often exhibit uncertainties that…

Data Analysis, Statistics and Probability · Physics 2017-12-07 Paul N. Patrone , Anthony J. Kearsley , Andrew M. Dienstfrey

Arguments are gived for the plausibility that quantum mechanics is a stochastic theory and that many quantum phenomena derive from the existence of a real noise consisting of vacuum fluctuations of all fundamental fields existing in nature.…

Quantum Physics · Physics 2016-09-26 Emilio Santos

Flow cytometry measurements are widely used in diagnostics and medical decision making. Incomplete understanding of sources of measurement uncertainty can make it difficult to distinguish autofluorescence and background sources from signals…

Quantitative Methods · Quantitative Biology 2024-12-02 Prajakta Bedekar , Megan A. Catterton , Matthew DiSalvo , Gregory A. Cooksey , Anthony J. Kearsley , Paul N. Patrone

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

Researchers at the National Institute of Standards and Technology have been using a watt balance, NIST-3, to measure the Planck constant $h$ for over ten years. Two recently published values disagree by more than one standard uncertainty.…

Instrumentation and Detectors · Physics 2015-06-23 S. Schlamminger , R. L. Steiner , D. Haddad , D. B. Newell , F. Seifert , L. S. Chao , R. Liu , E. R. Williams , J. R. Pratt

We present a method for computing uncertainties in spectral models, i.e. level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data. We provide analytic…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 Manuel A. Bautista , Vanessa Fivet , Pascal Quinet , Jay Dunn , Theodore R. Gull. Timothy R. Kallman , Claudio Mendoza

Some methods for the determination and the most precise values of constants of an extended Standard Model, which include the gravitation interaction and massive neutrinos, are presented. Accuracies of constants at different energy scales…

High Energy Physics - Phenomenology · Physics 2010-04-30 S. A. Kononogov , V. N. Melnikov , V. V. Khruschov

We explore a stochastic model that enables capturing external influences in two specific ways. The model allows for the expression of uncertainty in the parametrisation of the stochastic dynamics and incorporates patterns to account for…

Pricing of Securities · Quantitative Finance 2024-04-11 Felix L. Wolf , Griselda Deelstra , Lech A. Grzelak

The measurement of the Avogadro constant opened the way to a comparison of the watt-balance measurements of the Planck constant with the values calculated from the quotients of the Planck constant and the mass of a particle or an atom.…

Data Analysis, Statistics and Probability · Physics 2015-03-19 Enrico Massa , Giovanni Mana , Michael Jentschel