Related papers: A flexible method for estimating luminosity functi…
Landslide monitoring is essential for understanding geohazards and mitigating associated risks. Existing point cloud-based methods, however, typically rely on either geometric or radiometric information and often yield sparse or non-3D…
Photometric redshift surveys map the distribution of matter in the Universe through the positions and shapes of galaxies with poorly resolved measurements of their radial coordinates. While a tomographic analysis can be used to recover some…
In this paper, we develop a method for estimating and clustering two-dimensional spectral density functions (2D-SDFs) for spatial data from multiple subregions. We use a common set of adaptive basis functions to explain the similarities…
Monocular depth estimation (MDE) methods are often either too computationally expensive or not accurate enough due to the trade-off between model complexity and inference performance. In this paper, we propose a lightweight network that can…
Lensed quasars and supernovae can be used to study galaxies' gravitational potential and measure cosmological parameters. The typical image separation of objects lensed by galaxies is of the order of 0.5". Therefore, finding the ones with…
This paper introduces a new conceptual framework that recasts surface roughness effects as a "ray deflection function" (RDF) which can be statistically represented through a modified Zernike-Fourier hybrid approach that directly connects…
We present a measurement of the K-band luminosity function (LF) of field galaxies obtained from near-infrared imaging of a sample of 345 galaxies selected from the Stromlo-APM Redshift Survey. The LF is well-fitted over the ten magnitude…
We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1)…
Ordinary differential equation (ODE) is widely used in modeling biological and physical processes in science. In this article, we propose a new reproducing kernel-based approach for estimation and inference of ODE given noisy observations.…
(Abriged) We present a measurement of the evolution of the rest-frame K-band luminosity function to z ~ 1.2 using a sample of more than 5000 K-selected galaxies drawn from the MUNICS dataset. Distances and absolute K-band magnitudes are…
A Local Orthogonal Polynomial Expansion (LOrPE) of the empirical density function is proposed as a novel method to estimate the underlying density. The estimate is constructed by matching localized expectation values of orthogonal…
In contrast to current state-of-the-art methods, such as NSFP [25], which employ deep implicit neural functions for modeling scene flow, we present a novel approach that utilizes classical kernel representations. This representation enables…
Astronomical observations typically provide three-dimensional maps, encoding the distribution of the observed flux in (1) the two angles of the celestial sphere and (2) energy/frequency. An important task regarding such maps is to…
Markov Chain Monte Carlo approach is frequently used within Bayesian framework to sample the target posterior distribution. Its efficiency strongly depends on the proposal used to build the chain. The best jump proposal is the one that…
The composite galaxy luminosity function (hereafter LF) of 39 Abell clusters of galaxies is derived by computing the statistical excess of galaxy counts in the cluster direction with respect to control fields. Due to the wide field coverage…
Kernel density estimation is a convenient way to estimate the probability density of a distribution given the sample of data points. However, it has certain drawbacks: proper description of the density using narrow kernels needs large data…
Dense conditional random fields (CRF) with Gaussian pairwise potentials have emerged as a popular framework for several computer vision applications such as stereo correspondence and semantic segmentation. By modeling long-range…
In this paper we present a rigorous derivation of the luminosity function (LF) in presence of a background. Our approach is free from the logical contradictions of assigning negative values to positively defined quantities and avoid the use…
We present a simulation-based forward-modeling framework for cosmological inference from optical galaxy-cluster samples, and apply it to the abundance and weak-lensing signals of DES-Y1 redMaPPer clusters. The model embeds…
Redshift space distortions of the matter density power spectrum carry information on the growth rate of cosmic structure but require accurate modeling of nonlinear and velocity effects on the density field. We test and advance the…