相关论文: A generalizable method for estimating meteor showe…

The velocity distributions of stellar tracers in general exhibit weak non-Gaussianity encoding information on the orbital composition of a galaxy and the underlying potential. The standard solution for measuring non-Gaussianity involves…

This paper develops a density deconvolution estimator that assumes the density of interest is a member of the generalized skew-symmetric (GSS) family of distributions. Estimation occurs in two parts: a skewing function, as well as location…

We introduce a new nonparametric density estimator inspired by Markov Chains, and generalizing the well-known Kernel Density Estimator (KDE). Our estimator presents several benefits with respect to the usual ones and can be used…

This article describes our approach to quantifying the characteristics of meteors such as temperature, chemical composition, and others. We are using a new approach based on colourimetry. We analyze an image of Leonid meteor-6230 obtained…

Given points $p_1, \dots, p_n$ in $\mathbb{R}^d$, how do we find a point $x$ which maximizes $\frac{1}{n} \sum_{i=1}^n e^{-\|p_i - x\|^2}$? In other words, how do we find the maximizing point, or mode of a Gaussian kernel density estimation…

We develop a nonparametric two-sample test for distributions supported on the cone of symmetric positive definite matrices. The procedure relies on the Wishart kernel density estimator (KDE) introduced by Belzile et al. (2025), whose…

The disruption of asteroids and comets produces cm-sized meteoroids that end up impacting the Earth's atmosphere and producing bright fireballs that might have associated shock waves or, in geometrically-favorable occasions excavate craters…

Geminids are the most active annual meteor shower observed on Earth. Their parent is an active asteroid, (3200) Phaethon, which is a target of the planned DESTINY+ mission of the Japan Aerospace Exploration Agency (JAXA). The exact physical…

This paper investigates the problem of object detection with a focus on improving both the localization accuracy of bounding boxes and explicitly modeling prediction uncertainty. Conventional detectors rely on deterministic bounding box…

Meteors are important phenomenon reflecting many properties of interplanetary dust particles. The study of their origin, mass distribution, and orbit evolution all require large data volume, which can only be obtained using large meteor…

Infrasound monitoring has proved to be effective in detection of the meteor generated shock waves. When combined with optical observations of meteors, this technique is also reliable for detecting centimeter-sized meteoroids that usually…

This paper studies Kernel Density Estimation for a high-dimensional distribution $\rho(x)$. Traditional approaches have focused on the limit of large number of data points $n$ and fixed dimension $d$. We analyze instead the regime where…

Kernel density estimation is a popular method for estimating unseen probability distributions. However, the convergence of these classical estimators to the true density slows down in high dimensions. Moreover, they do not define meaningful…

A new meteor shower $\lambda$-Sculptorids produced by the comet 46P/Wirtanen was forecast for December 12, 2023. The predicted activity was highly uncertain, but generally considered to be low. Observations in Australia, New Zealand, and…

When estimating target parameters in nonparametric models with nuisance parameters, substituting the unknown nuisances with nonparametric estimators can introduce ``plug-in bias.'' Traditional methods addressing this suboptimal…

We have recorded a dataset of 24 centimeter-sized meteoroids detected simultaneously by video and infrasound to critically examine the ReVelle [1974] weak shock meteor infrasound model. We find that the effect of gravity wave perturbations…

Optical surveys have become increasingly adept at identifying candidate Tidal Disruption Events (TDEs) in large numbers, but classifying these generally requires extensive spectroscopic resources. Here we present $\texttt{tdescore}$, a…

One key issue in several astrophysical problems is the evaluation of the density probability function underlying an observational discrete data set. We here review two non-parametric density estimators which recently appeared in the…

Distributional comparison is a fundamental problem in statistical data analysis with numerous applications in a variety of scientific and engineering fields. Numerous methods exist for distributional comparison but kernel Stein's method has…

In this paper, we introduce a robust nonparametric density estimator combining the popular Kernel Density Estimation method and the Median-of-Means principle (MoM-KDE). This estimator is shown to achieve robustness to any kind of anomalous…