Results 21 to 30 of about 486 (135)

Autoencoding Galaxy Spectra. II. Redshift Invariance and Outlier Detection

The Astronomical Journal, 2023
We present an unsupervised outlier detection method for galaxy spectra based on the spectrum autoencoder architecture spender , which reliably captures spectral features and provides highly realistic reconstructions for SDSS galaxy spectra.
Yan Liang, Peter Melchior, Sicong Lu, Andy Goulding, Charlotte Ward   +4 more
doaj   +1 more source

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, Jonathan C. Tan, Chia-Jung Hsu, Ye Zhu   +3 more
doaj   +1 more source

TD-CARMA: Painless, Accurate, and Scalable Estimates of Gravitational Lens Time Delays with Flexible CARMA Processes

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, David A. van Dyk, Hyungsuk Tak, Aneta Siemiginowska   +3 more
doaj   +1 more source

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, Anthony R. Pullen, Rachel S. Somerville, Patrick C. Breysse, John C. Forbes, Shengqi Yang, Yin Li, Abhishek S. Maniyar   +7 more
doaj   +1 more source

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
wiley   +1 more source

Gaussian processes - a gentle introduction

, 2022
Slides presented at the Exoplanets Astrostatistics Summer School (12-16 Sept. 2022 in Geneva).
Vinesh Maguire Rajpaul
core   +1 more source

The next decade of astroinformatics and astrostatistics [PDF]

Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and ...
Siemiginowska, Aneta, Ford, Eric B., Kuhn, Michael, Fabbiano, Giuseppina, Law, Casey, Huppenkothen, Daniela, Mandel, Kaisey, Eadie, Gwendolyn, Scargle, Jeff, Avelino, Arturo, Burkhart, Blakesley, de Souza, Rafael S., James, David J., Finkbeiner, Douglas P., López-Morales, Mercedes, Yanamandra-Fisher, Padma A., Lee, Thomas, Lazio, Joseph, Borne, Kirk, van Dyk, David A., Cisewski-Kehe, Jessi, Moustakas, John, Stenning, David C., Ntampaka, Michelle, Fruscione, Antonella, Muna, Demitri, Graham, Matthew, Kashyap, Vinay, Peek, J. E. G., Feigelson, Eric, Civano, Francesca, Richards, Gordon, Trimble, Virginia, Stevens, Abbie, Goodman, Alyssa A., Mahabal, Ashish A., Taylor, Stephen R., Speagle, Joshua S., Budavari, Tamas, Hernquist, Lars, Chilingarian, Igor, Foreman-Mackey, Daniel, Loredo, Tom, Stassun, Keivan G., Portillo, Stephen K. N., Czekala, Ian, Freeman, Peter, Guenther, Hans Moritz, Meng, Xiao-Li, Hakkila, Jon, Tremblay, Grant R., Young, C. Alex   +51 more
core   +2 more sources

Listening to stars: audio-inspired multimodal learning for star classification

Frontiers in Astronomy and Space Sciences
Stellar spectral classification plays a crucial role in understanding the intrinsic properties of stars, such as their temperature, composition, and luminosity.
Shengwen Zhang, Shengwen Zhang, Yanxia Zhang, Chao Liu   +3 more
doaj   +1 more source

Stratified learning: A general‐purpose statistical method for improved learning under covariate shift

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, David A. van Dyk, Roberto Trotta, David C. Stenning   +3 more
wiley   +1 more source

Bayesian inference: more than Bayes’s theorem

Frontiers in Astronomy and Space Sciences
Bayesian 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
doaj   +1 more source