Related papers: A Statistical Approach to Quantifying Uncertainty …
This paper describes a recursive estimation procedure for multivariate binary densities (probability distributions of vectors of Bernoulli random variables) using orthogonal expansions. For $d$ covariates, there are $2^d$ basis coefficients…
We present a methodology for quantifying seismic velocity and pore pressure uncertainty that incorporates information regarding the geological history of a basin, rock physics, well log, drilling and seismic data. In particular, our…
Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are integral to many domains, e.g., indicators of valuable minerals are…
To determine the local dark matter density (LDMD) of the solar system is a classical problem in astronomy. Recently, a novel method of determining the LDMD from stellar distribution and vertical velocity dispersion profiles perpendicular to…
Gaia Data Release 2 (DR2) includes milliarcsecond-accuracy astrometry for 14,099 asteroids. We explore the practical impact of this data for the purpose of asteroid mass and orbit estimation by estimating the masses individually for four…
While deep neural networks have become the go-to approach in computer vision, the vast majority of these models fail to properly capture the uncertainty inherent in their predictions. Estimating this predictive uncertainty can be crucial,…
As a counterpoint to classical stochastic particle methods for linear diffusion equations, we develop a deterministic particle method for the weighted porous medium equation (WPME) and prove its convergence on bounded time intervals. This…
We study constraints that anticipated DEEP survey galaxy counts versus redshift data will place on cosmological model parameters in models with and without a constant or time-variable cosmological constant $\Lambda$. This data will result…
The Euclid mission of the European Space Agency will provide weak gravitational lensing and galaxy clustering surveys that can be used to constrain the standard cosmological model and its extensions, with an opportunity to test the…
Recent observational results suggest that our universe is nearly flat and well modelled within a $\Lambda$CDM framework. The observed values of $\Omega_{m}$ and $\Omega_{\Lambda}$ inevitably involve uncertainties. Motivated by this, we make…
We investigate the scattering and absorption of light by random ballistic aggregates of spherical monomers. We present a general measure for the porosity of an irregular particle. Three different classes of ballistic aggregates are…
In a previous article, we obtained the first-ever list of astrometric binary asteroid candidates. Some of these candidates have now been confirmed. In that previous work, however, the details of the statistical methods were not provided.…
Limited DXA access hinders osteoporosis screening. This proof-of-concept study proposes using widely available knee X-rays for opportunistic Bone Mineral Density (BMD) estimation via deep learning, emphasizing robust uncertainty…
We investigate the observation of meteors with video cameras in stratospheric balloons, overcoming tropospheric handicaps like weather and extinction. We have studied the practical implementation of the idea, designed and tested…
We develop a mixture-based approach to robust density modeling and outlier detection for experimental multivariate data that includes measurement error information. Our model is designed to infer atypical measurements that are not due to…
The study of meteoroid streams reveals the full complexity of these structures. At present, we have no objective method of deciding whether the parameters of the observed meteoroid stream represent a further solution to an already known…
In the event of a nuclear accident, or the detonation of a radiological dispersal device, quickly locating the source of the accident or blast is important for emergency response and environmental decontamination. At a specified time after…
Theoretical uncertainties on non-linear scales are among the main obstacles to exploit the sensitivity of forthcoming galaxy and hydrogen surveys like Euclid or the Square Kilometre Array (SKA). Here, we devise a new method to model the…
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…
We present an analysis of the accuracy of geometric albedos determined for asteroids through the modeling of observed thermal infrared radiation. We show that albedo uncertainty is dominated by the uncertainty on the measured $H_V$ absolute…