Homogeneous Stellar Parameters from Heterogeneous Spectra with Deep Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Shen, Jeff, Speagle, Joshua S., Ho, Shirley |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Closing the stellar labels gap: Stellar label independent evidence for [$α/M$] information in Gaia BP/RP spectra
by: Laroche, Alexander, et al.
Published: (2024)
by: Laroche, Alexander, et al.
Published: (2024)
Photometric Completeness Modelled With Neural Networks
by: Harris, William E., et al.
Published: (2024)
by: Harris, William E., et al.
Published: (2024)
Disk Wind Feedback from High-mass Protostars. V. Application of Multi-Modal Machine Learning to Characterize Outflow Properties
by: Xu, Duo, et al.
Published: (2026)
by: Xu, Duo, et al.
Published: (2026)
Stellar Atmospheric Parameters From Gaia BP/RP Spectra using Uncertain Neural Networks
by: Fallows, Connor P., et al.
Published: (2024)
by: Fallows, Connor P., et al.
Published: (2024)
SpectraFM: Tuning into Stellar Foundation Models
by: Koblischke, Nolan, et al.
Published: (2024)
by: Koblischke, Nolan, et al.
Published: (2024)
A CNN--Transformer Denoiser for low-$S/N$ Galaxy Spectra: Stellar Population Recovery in Synthetic Tests
by: Kim, Suk, et al.
Published: (2026)
by: Kim, Suk, et al.
Published: (2026)
An Empirical Sample of Spectra of M-type Stars with Homogeneous Atmospheric-Parameter Labels
by: Du, Bing, et al.
Published: (2024)
by: Du, Bing, et al.
Published: (2024)
Resolved Stellar Mass Estimation of Nearby Late-type Galaxies for the SPHEREx Era: Dependence on Stellar Population Synthesis Models
by: Lee, Jeong Hwan, et al.
Published: (2025)
by: Lee, Jeong Hwan, et al.
Published: (2025)
Galaxy Spectra neural Network (GaSNet). II. Using Deep Learning for Spectral Classification and Redshift Predictions
by: Zhong, Fucheng, et al.
Published: (2023)
by: Zhong, Fucheng, et al.
Published: (2023)
Filter Design for Estimation of Stellar Metallicity: Insights from Experiments with Gaia XP Spectra
by: Xiao, Kai, et al.
Published: (2024)
by: Xiao, Kai, et al.
Published: (2024)
Deep Multimodal Representation Learning for Stellar Spectra
by: Buck, Tobias, et al.
Published: (2024)
by: Buck, Tobias, et al.
Published: (2024)
Parameter Recovery Study on IZI -- a Bayesian Analysis Tool for Emission Lines from H II Regions and Star-forming Galaxies
by: Shinn, Jong-Ho, et al.
Published: (2025)
by: Shinn, Jong-Ho, et al.
Published: (2025)
The first catalog of candidate white dwarf-main sequence binaries in open star clusters: A new window into common envelope evolution
by: Grondin, Steffani M., et al.
Published: (2024)
by: Grondin, Steffani M., et al.
Published: (2024)
$\mbox{H}$ $\mbox{I}$ 21-cm Absorption Spectra Classification using Machine Learning
by: Mondal, Debasish, et al.
Published: (2025)
by: Mondal, Debasish, et al.
Published: (2025)
Deriving Stellar Properties, Distances, and Reddenings using Photometry and Astrometry with BRUTUS
by: Speagle, Joshua S., et al.
Published: (2025)
by: Speagle, Joshua S., et al.
Published: (2025)
CSST Slitless Spectra: Target Detection and Classification with YOLO
by: Zhou, Yingying, et al.
Published: (2025)
by: Zhou, Yingying, et al.
Published: (2025)
DeepDISC-Euclid: Source Classification and Photometric Redshifts in Euclid Deep Field North With a Pixel-Level Deep Learning Approach
by: Jiang, Yuanzhe, et al.
Published: (2026)
by: Jiang, Yuanzhe, et al.
Published: (2026)
200,000+ Deep Learning-inferred Periods of Stellar Variability from the All-Sky Automated Survey for Supernovae
by: Schochet, Meir E., et al.
Published: (2025)
by: Schochet, Meir E., et al.
Published: (2025)
Latent Stochastic Differential Equations for Modeling Quasar Variability and Inferring Black Hole Properties
by: Fagin, Joshua, et al.
Published: (2023)
by: Fagin, Joshua, et al.
Published: (2023)
The Redshifts from 122 Bands: Comparative Redshift Forecast for Low-Resolution Spectra from SPHEREx and 7-Dimensional Sky Survey (7DS)
by: Bae, Jangho, et al.
Published: (2025)
by: Bae, Jangho, et al.
Published: (2025)
Data-Driven Stellar Spectral Modelling with GSPICE
by: Finkbeiner, Douglas P., et al.
Published: (2025)
by: Finkbeiner, Douglas P., et al.
Published: (2025)
Stellar Parameters for over Fifty Million stars from SMSS DR4 and Gaia DR3
by: Huang, Yang, et al.
Published: (2025)
by: Huang, Yang, et al.
Published: (2025)
Resolving Galaxy Nuclei and Compact Stellar Systems as Engines of Galaxy Evolution
by: Lamprecht, Julia, et al.
Published: (2025)
by: Lamprecht, Julia, et al.
Published: (2025)
Infrared Spectra of Solid-State Ethanolamine: Laboratory Data in Support of JWST Observations
by: Suhasaria, T., et al.
Published: (2024)
by: Suhasaria, T., et al.
Published: (2024)
VUV Processing of Nitrile Ice: Direct Comparison of Branching in Ice and TPD Spectra
by: Hager, Travis J., et al.
Published: (2025)
by: Hager, Travis J., et al.
Published: (2025)
J-PAS: A Neural Network Approach to Single Stellar Population Characterization
by: Sánchez, H. Domínguez, et al.
Published: (2025)
by: Sánchez, H. Domínguez, et al.
Published: (2025)
Modeling Globular Cluster Stellar Streams with a Basis-Expansion N-body Code
by: Cook, Brian T., et al.
Published: (2026)
by: Cook, Brian T., et al.
Published: (2026)
Simulating the Stellar Bycatch: Constraining the Prevalence of Extraterrestrial Transmitters within Radio SETI Surveys
by: Mason, Louisa A., et al.
Published: (2025)
by: Mason, Louisa A., et al.
Published: (2025)
NIRDust: Probing Hot Dust Emission Around Type 2 AGN Using K-band Spectra
by: Gaspar, Gaia, et al.
Published: (2024)
by: Gaspar, Gaia, et al.
Published: (2024)
Machine Learning in Stellar Astronomy: Progress up to 2024
by: Li, Guangping, et al.
Published: (2025)
by: Li, Guangping, et al.
Published: (2025)
Mining for Protoclusters at $z\sim4$ from Photometric Datasets with Deep Learning
by: Takeda, Yoshihiro, et al.
Published: (2024)
by: Takeda, Yoshihiro, et al.
Published: (2024)
The High-Resolution Far- to Near-Infrared Anharmonic Absorption Spectra of Cyano-Substituted Polycyclic Aromatic Hydrocarbons from 300-6200 cm$^{-1}$
by: Esposito, Vincent J., et al.
Published: (2024)
by: Esposito, Vincent J., et al.
Published: (2024)
Estimating Stellar Atmospheric Parameters and [α/Fe] for LAMOST O-M type Stars Using a Spectral Emulator
by: Liang, Jun-chao, et al.
Published: (2024)
by: Liang, Jun-chao, et al.
Published: (2024)
Emulating CO Line Radiative Transfer with Deep Learning
by: Su, Shiqi, et al.
Published: (2025)
by: Su, Shiqi, et al.
Published: (2025)
Fast and Accurate Stellar Mass Predictions from Broad-Band Magnitudes with a Simple Neural Network: Application to Simulated Star-Forming Galaxies
by: Elson, E.
Published: (2025)
by: Elson, E.
Published: (2025)
Galactic Alchemy: Deep Learning Map-to-Map Translation in Hydrodynamical Simulations
by: Denzel, Philipp, et al.
Published: (2025)
by: Denzel, Philipp, et al.
Published: (2025)
Deep Learning Improves Photometric Redshifts in All Regions of Color Space
by: Moran, Emma R., et al.
Published: (2025)
by: Moran, Emma R., et al.
Published: (2025)
Optimizing Deep Learning Photometric Redshifts for the Roman Space Telescope with HST/CANDELS
by: Khederlarian, Ashod, et al.
Published: (2026)
by: Khederlarian, Ashod, et al.
Published: (2026)
First Discovery and Confirmation of PN Candidates Found from AI and Deep Learning Techniques Applied to VPHAS+ Survey Data
by: Li, Yushan, et al.
Published: (2024)
by: Li, Yushan, et al.
Published: (2024)
Why the Northern Hemisphere Needs a 30-40 m Telescope and the Science at Stake: Resolved Stellar Populations Studies in M31 and its Satellites
by: Gallart, C., et al.
Published: (2025)
by: Gallart, C., et al.
Published: (2025)
Similar Items
-
Closing the stellar labels gap: Stellar label independent evidence for [$α/M$] information in Gaia BP/RP spectra
by: Laroche, Alexander, et al.
Published: (2024) -
Photometric Completeness Modelled With Neural Networks
by: Harris, William E., et al.
Published: (2024) -
Disk Wind Feedback from High-mass Protostars. V. Application of Multi-Modal Machine Learning to Characterize Outflow Properties
by: Xu, Duo, et al.
Published: (2026) -
Stellar Atmospheric Parameters From Gaia BP/RP Spectra using Uncertain Neural Networks
by: Fallows, Connor P., et al.
Published: (2024) -
SpectraFM: Tuning into Stellar Foundation Models
by: Koblischke, Nolan, et al.
Published: (2024)