Results 21 to 30 of about 526 (97)
Genetic Algorithm Modeling with GPU Parallel Computing Technology [PDF]
, 2012 We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel computing technology. The model was derived from a multi-core CPU serial implementation, named GAME, already scientifically successfully tested and ...
Brescia, Massimo +5 more
core +2 more sources
Introduction to papers on astrostatistics
, 2009 We are pleased to present a Special Section on Statistics and Astronomy in this issue of the The Annals of Applied Statistics. Astronomy is an observational rather than experimental science; as a result, astronomical data sets both small and large ...
Loredo, Thomas J. +2 more
core +1 more source
Bayesian astrostatistics: a backward look to the future
, 2012 This perspective chapter briefly surveys: (1) past growth in the use of Bayesian methods in astrophysics; (2) current misconceptions about both frequentist and Bayesian statistical inference that hinder wider adoption of Bayesian methods by astronomers ...
A Gelman +41 more
core +1 more source
An analysis of feature relevance in the classification of astronomical transients with machine learning methods [PDF]
, 2016 The exploitation of present and future synoptic (multi-band and multi-epoch) surveys requires an extensive use of automatic methods for data processing and data interpretation.
Brescia, Massimo +6 more
core +4 more sources
Statistical Issues Often Overlooked when Analyzing Astronomical Data
The Astrophysical Journal Supplement SeriesThe main topics covered in this paper are (1) controlling significance levels when applying the same hypothesis test to many (possibly millions) of datasets; (2) dealing with the fact that for very large datasets hypotheses are rejected for trivially ...
C. Koen
doaj +1 more source
Are tiled display walls needed for astronomy? [PDF]
, 2014 Clustering commodity displays into a Tiled Display Wall (TDW) provides a cost-effective way to create an extremely high resolution display, capable of approaching the image sizes now gen- erated by modern astronomical instruments.
Fluke, Christopher J +3 more
core +1 more source
Statistical Analysis and Data Mining: The ASA Data Science Journal, Volume 17, Issue 1, February 2024.Abstract We propose a simple, statistically principled, and theoretically justified method to improve supervised learning when the training set is not representative, a situation known as covariate shift. We build upon a well‐established methodology in causal inference and show that the effects of covariate shift can be reduced or eliminated by ...
Maximilian Autenrieth +3 more
wiley +1 more source
The Astrophysical JournalEmulators using machine learning techniques have emerged to efficiently generate mock data matching the large survey volume for upcoming experiments, as an alternative approach to large-scale numerical simulations.
Kangning Diao, Yi Mao
doaj +1 more source
On high-frequency limits of $U$-statistics in Besov spaces over compact manifolds [PDF]
, 2016 In this paper, quantitative bounds in high-frequency central limit theorems are derived for Poisson based $U$-statistics of arbitrary degree built by means of wavelet coefficients over compact Riemannian manifolds. The wavelets considered here are the so-
Bourguin, Solesne, Durastanti, Claudio
core +2 more sources
Photometric Redshift Estimation of Quasars by a Cross-modal Contrast Learning Method
The Astronomical JournalEstimating photometric redshifts (photo- z ) of quasars is crucial for measuring cosmic distances and monitoring cosmic evolution. While numerous point estimation methods have successfully determined photo- z , they often struggle with the inherently ill-
Chen Zhang +4 more
doaj +1 more source