Results 31 to 40 of about 379 (121)
A Statistical Search for a Uniform Trigger Threshold in Solar Flares from Individual Active Regions
The Astrophysical Journal, 2023 Solar flares result from the sudden release of energy deposited by subphotospheric motions into the magnetic field of the corona. The deposited energy accumulates secularly between events. One may interpret the observed event statistics as resulting from
Julian B. Carlin +2 more
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Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds
The Astrophysical Journal, 2023 We introduce the state-of-the-art deep-learning denoising diffusion probabilistic model as a method to infer the volume or number density of giant molecular clouds (GMCs) from projected mass surface density maps.
Duo Xu +3 more
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The Astrophysical Journal, 2023 Cosmological parameters encoding our understanding of the expansion history of the universe can be constrained by the accurate estimation of time delays arising in gravitationally lensed systems.
Antoine D. Meyer +3 more
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Characterizing the Conditional Galaxy Property Distribution Using Gaussian Mixture Models
The Astrophysical Journal, 2023 Line-intensity mapping (LIM) is a promising technique to constrain the global distribution of galaxy properties. To combine LIM experiments probing different tracers with traditional galaxy surveys and fully exploit the scientific potential of these ...
Yucheng Zhang +7 more
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Robust joint modelling of sparsely observed paired functional data
Canadian Journal of Statistics, Volume 52, Issue 3, Page 734-754, September 2024.Abstract A reduced‐rank mixed‐effects model is developed for robust modelling of sparsely observed paired functional data. In this model, the curves for each functional variable are summarized using a few functional principal components, and the association of the two functional variables is modelled through the association of the principal component ...
Huiya Zhou, Xiaomeng Yan, Lan Zhou
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Bayesian inference: more than Bayes’s theorem
Frontiers in Astronomy and Space SciencesBayesian inference gets its name from Bayes’s theorem, expressing posterior probabilities for hypotheses about a data generating process as the (normalized) product of prior probabilities and a likelihood function.
Thomas J. Loredo, Robert L. Wolpert
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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
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Listening to stars: audio-inspired multimodal learning for star classification
Frontiers in Astronomy and Space SciencesStellar spectral classification plays a crucial role in understanding the intrinsic properties of stars, such as their temperature, composition, and luminosity.
Shengwen Zhang +3 more
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Bayesian Functional Data Analysis in Astronomy
Physical Sciences ForumCosmic demographics—the statistical study of populations of astrophysical objects—has long relied on tools from multivariate statistics for analyzing data comprising fixed-length vectors of properties of objects, as might be compiled in a tabular ...
Thomas Loredo +3 more
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Big data and paradigm shift for astronomy in the 21stcentury
大数据, 2016 With the development of large space-based and ground-based observational technologies,the volume,output rate and complexity of astronomical data rapidly increase.The astronomy steps into a new data-intensive era.The characteristics of astronomical data ...
Yanxia ZHANG +2 more
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