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A variable speed of light (VSL) cosmology is described in which the causal mechanism of generating primordial perturbations is achieved by varying the speed of light in a primordial epoch. This yields an alternative to inflation for…

Cosmology and Nongalactic Astrophysics · Physics 2016-03-20 J. W. Moffat

A model independent parametrization of an extension of the Standard Model including vector-like quarks, new heavy gauge bosons and an extra scalar, is introduced. Theoretical constraints on the model couplings and hypothetical particle…

High Energy Physics - Phenomenology · Physics 2025-09-09 Chahra Rekaik , Mohamed Sadek Zidi

Time series forecasting aids decision-making, especially for stakeholders who rely on accurate predictions, making it very important to understand and explain these models to ensure informed decisions. Traditional explainable AI (XAI)…

Computation and Language · Computer Science 2024-10-22 Taha Aksu , Chenghao Liu , Amrita Saha , Sarah Tan , Caiming Xiong , Doyen Sahoo

We propose a new technique to measure the time delay of radio-loud gravitational lens systems, which does not rely on the excessive use of interferometric observations. Instead, the method is based on single-dish flux density monitoring of…

Astrophysics · Physics 2015-06-24 Bernhard Geiger , Peter Schneider

Recent work proposed the computation of so-called PI-explanations of Naive Bayes Classifiers (NBCs). PI-explanations are subset-minimal sets of feature-value pairs that are sufficient for the prediction, and have been computed with…

Machine Learning · Computer Science 2020-11-05 Joao Marques-Silva , Thomas Gerspacher , Martin C. Cooper , Alexey Ignatiev , Nina Narodytska

This paper discusses model order reduction of LTI systems over limited frequency intervals within the framework of balanced truncation. Two new \emph{frequency-dependent balanced truncation} methods were developed, one is \emph{SF-type…

Systems and Control · Computer Science 2016-02-16 Xin Du , Peter Benner

This study focuses on exploring the use of local interpretability methods for explaining time series clustering models. Many of the state-of-the-art clustering models are not directly explainable. To provide explanations for these…

Machine Learning · Computer Science 2022-08-03 Ozan Ozyegen , Nicholas Prayogo , Mucahit Cevik , Ayse Basar

The Cosmic Radio Dipole is of fundamental interest to cosmology. Recent studies revealed open questions about the nature of the observed Cosmic Radio Dipole. We use simulated source count maps to test a linear and a quadratic estimator for…

Cosmology and Nongalactic Astrophysics · Physics 2021-12-07 Thilo M. Siewert , Matthias Schmidt-Rubart , Dominik J. Schwarz

The potential of gravitational lenses for providing direct, physical measurements of the Hubble constant, free from systematic errors associated with the traditional distance ladder, has long been recognized. However, it is only recently…

Astrophysics · Physics 2007-05-23 Roger D. Blandford , Tomislav Kundic

We present a noise deconvolution technique for obtaining noiseless expectation values of noisy observables at the output of multiqubit quantum channels. For any number of qubits or in the presence of correlations, our protocol applies to…

Quantum Physics · Physics 2023-02-14 Simone Roncallo , Lorenzo Maccone , Chiara Macchiavello

Large language Models (LLMs) have achieved significant breakthroughs across diverse domains; however, they can still produce unreliable or misleading outputs. For responsible LLM application, Uncertainty Quantification (UQ) techniques are…

Machine Learning · Computer Science 2026-05-15 Qihao Wen , Jiahao Wang , Yang Nan , Pengfei He , Ravi Tandon , Han Xu

We consider the problem of parameterizing Newman-type models of Li-ion batteries focusing on quantifying the inherent uncertainty of this process and its dependence on the discharge rate. In order to rule out genuine experimental error and…

Computational Physics · Physics 2021-04-14 Jose Morales Escalante , Smita Sahu , Jamie M. Foster , Bartosz Protas

Models of spontaneous wavefunction collapse explain the quantum-to-classical transition without invoking the von Neumann measurement postulate. Prominent frameworks, such as the Di\'osi-Penrose (DP) and Continuous Spontaneous Localization…

Quantum Physics · Physics 2025-04-09 Nicola Bortolotti , Catalina Curceanu , Lajos Diósi , Simone Manti , Kristian Piscicchia

Atmospheric aerosols influence the Earth's climate, primarily by affecting cloud formation and scattering visible radiation. However, aerosol-related physical processes in climate simulations are highly uncertain. Constraining these…

Very long baseline interferometry (VLBI) provides the resolution needed to make precision measurements of a pulsar's parallax and proper motion. In making these measurements, the astronomer is faced with difficult calibration problems and a…

Astrophysics · Physics 2007-05-23 Walter Brisken

Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task. In this work, we show that explicitly quantifying the uncertainty in…

Machine Learning · Computer Science 2019-10-08 Asma Ghandeharioun , Brian Eoff , Brendan Jou , Rosalind W. Picard

Time delays in gravitational lenses can be used to determine the Hubble constant and the lens potential. In future surveys, many gravitational lenses can be discovered, and their time delays and image positions can in principle be measured.…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-10 Hans Witt , Shude Mao

The determination of |Vub| from inclusive semileptonic B decays is limited by uncertainties in modelling the decay distributions in b->ulnu transitions. The largest uncertainties arise from the limited knowledge of the appropriate b quark…

High Energy Physics - Experiment · Physics 2010-04-05 Robert V. Kowalewski , Sven Menke

Using a dynamical model to make predictions about a system has many sources of error. These can include errors in how the model was initialised but also errors in the dynamics of the model itself. For many applications in data assimilation,…

Numerical Analysis · Mathematics 2025-07-07 P. A. Browne

We propose a differentiable imaging framework to address uncertainty in measurement coordinates such as sensor locations and projection angles. We formulate the problem as measurement interpolation at unknown nodes supervised through the…

Image and Video Processing · Electrical Eng. & Systems 2023-12-21 Sidharth Gupta , Konik Kothari , Valentin Debarnot , Ivan Dokmanić