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The study of the visible colours of the trans-Neptunian objects opened a discussion almost 20 years ago which, in spite of the increase in the amount of available data, seems far from subside. Visible colours impose constraints to the…

Earth and Planetary Astrophysics · Physics 2019-07-17 Alvaro Alvarez-Candal , Carmen Ayala-Loera , Ricardo Gil-Hutton , José Luis Ortiz , Pablo Santos-Sanz , René Duffard

In the context of difference image analysis (DIA), we present a new method for determining the convolution kernel matching a pair of images of the same field. Unlike the standard DIA technique which involves modelling the kernel as a linear…

Astrophysics · Physics 2009-11-13 D. M. Bramich

We present improved measurements of the branching fractions of the color-suppressed decays $\bar{B}^0 \to D^{(*)0} h^{0}$ where $h^{0}$ represents a light neutral meson $\pi^{0}$, $\eta$ or $\omega$. The measurements are based on a data…

High Energy Physics - Experiment · Physics 2019-08-14 S. Blyth

A novel hybrid method based on Mie theory and the Discrete Dipole Approximation (DDA) was developed to study the microscopic parameters governing the optical response of tunable photonic crystals (PC). The method is based on a two-step…

One major challenge in machine learning applications is coping with mismatches between the datasets used in the development and those obtained in real-world applications. These mismatches may lead to inaccurate predictions and errors,…

Machine Learning · Statistics 2023-09-01 Keisuke Kawano , Takuro Kutsuna , Ryoko Tokuhisa , Akihiro Nakamura , Yasushi Esaki

The influence of ns-laser wavelength to discriminate ancient painting techniques such as are fresco, casein, animal glue, egg yolk and oil was investigated in this work. This study was carried out with a single shot laser on samples covered…

We describe a variant of the dressing method giving alternative representation of multidimensional nonlinear PDE as a system of Integro-Differential Equations (IDEs) for spectral and dressing functions. In particular, it becomes single…

Analysis of PDEs · Mathematics 2016-09-07 A. I. Zenchuk

Neutrino non-standard interactions (NSI) with the first generation of standard model fermions can span a parameter space of large dimension and exhibit degeneracies that cannot be broken by a single class of experiment. Oscillation…

High Energy Physics - Phenomenology · Physics 2020-09-22 Bhaskar Dutta , Rafael F. Lang , Shu Liao , Samiran Sinha , Louis Strigari , Adrian Thompson

Out-of-distribution (OOD) detection in multimodal contexts is essential for identifying deviations in combined inputs from different modalities, particularly in applications like open-domain dialogue systems or real-life dialogue…

Computation and Language · Computer Science 2024-11-01 Rena Gao , Xuetong Wu , Siwen Luo , Caren Han , Feng Liu

The ESO-Spitzer extragalactic Imaging Survey (ESIS) is the optical follow up of the Spitzer Wide-Area InfraRed Extragalactic (SWIRE) survey in the ELAIS-S1 area. This paper presents B, V, R Wide Field Imager observations of the first 1.5…

Second-order PDE models have been widely used for suppressing multiplicative noise, but they often introduce blocky artifacts in the early stages of denoising. To resolve this, we propose a fourth-order nonlinear PDE model that integrates…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Rajendra K. Ray , Manish Kumar

Pulse Shape Discrimination (PSD) is a widely used technique in many experimental analysis. In this study, we specifically aimed to assess the effectiveness of PSD in accurately measuring decay time. We measured the decay times of a 0.1 wt%…

High Energy Physics - Experiment · Physics 2024-10-29 S. B. Hong , J. S. Park

Recent results on the Coherent Elastic Neutrino-Nucleus Scattering (CE$\nu$NS) on germanium present significant discrepancies among experiments. We perform a combined analysis of the Dresden-II, CONUS+ and COHERENT data, quantifying the…

High Energy Physics - Phenomenology · Physics 2025-05-02 Yulun Li , Gonzalo Herrera , Patrick Huber

Ordinary differential equations (ODEs), via their induced flow maps, provide a powerful framework to parameterize invertible transformations for the purpose of representing complex probability distributions. While such models have achieved…

Statistics Theory · Mathematics 2023-09-06 Youssef Marzouk , Zhi Ren , Sven Wang , Jakob Zech

We consider treatment-effect estimation with a two-periods panel, where units are untreated at period one, and receive strictly positive doses at period two. First, we consider designs with some quasi-untreated units, with a period-two dose…

Econometrics · Economics 2026-04-02 Clément de Chaisemartin , Diego Ciccia , Xavier D'Haultfœuille , Felix Knau

Irregular sampling intervals and missing values in real-world time series data present challenges for conventional methods that assume consistent intervals and complete data. Neural Ordinary Differential Equations (Neural ODEs) offer an…

Machine Learning · Computer Science 2025-01-28 YongKyung Oh , Dong-Young Lim , Sungil Kim

We use 1169 Pan-STARRS supernovae (SNe) and 195 low-$z$ ($z < 0.1$) SNe Ia to measure cosmological parameters. Though most Pan-STARRS SNe lack spectroscopic classifications, in a previous paper (I) we demonstrated that photometrically…

Negative afterimage appears in our vision when we shift our gaze from an over stimulated original image to a new area with a uniform color. The colors of negative afterimages differ from the old stimulating colors in the original image when…

Computer Vision and Pattern Recognition · Computer Science 2017-09-15 Jinhui Yu , Kailin Wu , Kang Zhang , Xianjun Sam Zheng

Scene change detection (SCD), a crucial perception task, identifies changes by comparing scenes captured at different times. SCD is challenging due to noisy changes in illumination, seasonal variations, and perspective differences across a…

Computer Vision and Pattern Recognition · Computer Science 2022-08-12 Vijaya Raghavan T. Ramkumar , Elahe Arani , Bahram Zonooz

Neural Stochastic Differential Equations (NSDEs) model the drift and diffusion functions of a stochastic process as neural networks. While NSDEs are known to make accurate predictions, their uncertainty quantification properties have been…

Machine Learning · Computer Science 2022-09-13 Andreas Look , Melih Kandemir , Barbara Rakitsch , Jan Peters
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