Saved in:
| Main Authors: | Sedaghat, Nima, Romaniello, Martino, Carrick, Jonathan E., Pineau, François-Xavier |
|---|---|
| Format: | Preprint |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2009.12872 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stellar Karaoke: deep blind separation of terrestrial atmospheric effects out of stellar spectra by velocity whitening
by: Sedaghat, Nima, et al.
Published: (2023)
by: Sedaghat, Nima, et al.
Published: (2023)
Homogeneous Stellar Parameters from Heterogeneous Spectra with Deep Learning
by: Shen, Jeff, et al.
Published: (2026)
by: Shen, Jeff, et al.
Published: (2026)
Stellar parameter prediction and spectral simulation using machine learning
by: Cvrček, Vojtěch, et al.
Published: (2024)
by: Cvrček, Vojtěch, et al.
Published: (2024)
deep-REMAP: Probabilistic Parameterization of Stellar Spectra Using Regularized Multi-Task Learning
by: Gilda, Sankalp
Published: (2025)
by: Gilda, Sankalp
Published: (2025)
Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference
by: Lu, Hai-Ling, et al.
Published: (2026)
by: Lu, Hai-Ling, et al.
Published: (2026)
Adaptive Data Reduction Workflows for Astronomy -- The ESO Data Processing System (EDPS)
by: Freudling, Wolfram, et al.
Published: (2023)
by: Freudling, Wolfram, et al.
Published: (2023)
Predicting Stellar Parameters of Massive Stars from Light Curves with Machine Learning
by: Zhang, Rachel C., et al.
Published: (2025)
by: Zhang, Rachel C., et al.
Published: (2025)
Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics
by: Sedaghat, Nima, et al.
Published: (2024)
by: Sedaghat, Nima, et al.
Published: (2024)
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)
OmniSpectra: A Unified Foundation Model for Native Resolution Astronomical Spectra
by: Islam, Md Khairul, et al.
Published: (2026)
by: Islam, Md Khairul, et al.
Published: (2026)
Finetuning Stellar Spectra Foundation Models with LoRA
by: Zhao, Xiaosheng, et al.
Published: (2025)
by: Zhao, Xiaosheng, et al.
Published: (2025)
SpectraFM: Tuning into Stellar Foundation Models
by: Koblischke, Nolan, et al.
Published: (2024)
by: Koblischke, Nolan, et al.
Published: (2024)
Scaling Laws for Emulation of Stellar Spectra
by: Różański, Tomasz, et al.
Published: (2025)
by: Różański, Tomasz, et al.
Published: (2025)
SM-Net: Learning a Continuous Spectral Manifold from Multiple Stellar Libraries
by: Anwar, Omar, et al.
Published: (2026)
by: Anwar, Omar, et al.
Published: (2026)
InferA: A Smart Assistant for Cosmological Ensemble Data
by: Tam, Justin Z., et al.
Published: (2025)
by: Tam, Justin Z., et al.
Published: (2025)
A Machine Learning Framework for Stellar Collision Transient Identification
by: Hu, Betty X., et al.
Published: (2025)
by: Hu, Betty X., et al.
Published: (2025)
FLARE: A Framework for Stellar Flare Forecasting using Stellar Physical Properties and Historical Records
by: Zhu, Bingke, et al.
Published: (2025)
by: Zhu, Bingke, et al.
Published: (2025)
Rapid Parameter Estimation for Extreme Mass Ratio Inspirals Using Machine Learning
by: Liang, Bo, et al.
Published: (2024)
by: Liang, Bo, et al.
Published: (2024)
Data-Driven Modeling of Telluric Features and Stellar Variability with StellarSpectraObservationFitting.jl
by: Gilbertson, Christian, et al.
Published: (2024)
by: Gilbertson, Christian, 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)
Deep Multimodal Representation Learning for Stellar Spectra
by: Buck, Tobias, et al.
Published: (2024)
by: Buck, Tobias, 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)
Toward Robust Corrections for Stellar Contamination in JWST Exoplanet Transmission Spectra
by: Rackham, Benjamin V., et al.
Published: (2023)
by: Rackham, Benjamin V., et al.
Published: (2023)
$\mbox{H}$ $\mbox{I}$ 21-cm Absorption Spectra Classification using Machine Learning
by: Mondal, Debasish, et al.
Published: (2025)
by: Mondal, Debasish, et al.
Published: (2025)
Radiometer Calibration using Machine Learning
by: Leeney, S. A. K., et al.
Published: (2025)
by: Leeney, S. A. K., et al.
Published: (2025)
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)
Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks
by: Ballester, Manuel, et al.
Published: (2026)
by: Ballester, Manuel, et al.
Published: (2026)
Inferring Fireball Velocity Profiles and Characteristic Parameters of Meteoroids from Incomplete Datasets
by: Peña-Asensio, Eloy, et al.
Published: (2025)
by: Peña-Asensio, Eloy, et al.
Published: (2025)
Unsupervised Machine Learning for the Classification of Astrophysical X-ray Sources
by: Pérez-Díaz, Víctor Samuel, et al.
Published: (2024)
by: Pérez-Díaz, Víctor Samuel, et al.
Published: (2024)
Empirically Constraining the Spectra of Stellar Surface Features Using Time-Resolved Spectroscopy
by: Berardo, David, et al.
Published: (2023)
by: Berardo, David, et al.
Published: (2023)
A Bayesian Approach to Inferring Accretion Signatures in Young Stellar Objects: A Case Study with VIRUS
by: Willett, Lauren Halstead, et al.
Published: (2025)
by: Willett, Lauren Halstead, et al.
Published: (2025)
The case for an all-sky millimetre survey at sub-arcminute resolution
by: Désert, François-Xavier, et al.
Published: (2024)
by: Désert, François-Xavier, et al.
Published: (2024)
A Generative Model for Disentangling Galaxy Photometric Parameters
by: Leung, Keen, et al.
Published: (2025)
by: Leung, Keen, et al.
Published: (2025)
On the Performances of Estimating Stellar Atmospheric Parameters from CSST Broad-band Photometry
by: Shi, Ruifeng, et al.
Published: (2024)
by: Shi, Ruifeng, et al.
Published: (2024)
Inferring Planet and Disk Parameters from Protoplanetary Disk Images Using a Variational Autoencoder
by: Mahmud, Sayed Shafaat, et al.
Published: (2025)
by: Mahmud, Sayed Shafaat, et al.
Published: (2025)
TheUse of Conditional Variational Autoencoders in Generating Stellar Spectra
by: Gebran, Marwan, et al.
Published: (2025)
by: Gebran, Marwan, et al.
Published: (2025)
Encapsulating Textual Contents into a MOC data Structure for Advanced Applications
by: Greco, Giuseppe, et al.
Published: (2025)
by: Greco, Giuseppe, et al.
Published: (2025)
Fried Parameter Estimation from Single Wavefront Sensor Image with Artificial Neural Networks
by: Smith, Jeffrey, et al.
Published: (2025)
by: Smith, Jeffrey, et al.
Published: (2025)
FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation
by: Zhang, Bin, et al.
Published: (2026)
by: Zhang, Bin, et al.
Published: (2026)
Self-supervised Synthetic Pretraining for Inference of Stellar Mass Embedded in Dense Gas
by: Hirashima, Keiya, et al.
Published: (2025)
by: Hirashima, Keiya, et al.
Published: (2025)
Similar Items
-
Stellar Karaoke: deep blind separation of terrestrial atmospheric effects out of stellar spectra by velocity whitening
by: Sedaghat, Nima, et al.
Published: (2023) -
Homogeneous Stellar Parameters from Heterogeneous Spectra with Deep Learning
by: Shen, Jeff, et al.
Published: (2026) -
Stellar parameter prediction and spectral simulation using machine learning
by: Cvrček, Vojtěch, et al.
Published: (2024) -
deep-REMAP: Probabilistic Parameterization of Stellar Spectra Using Regularized Multi-Task Learning
by: Gilda, Sankalp
Published: (2025) -
Spectra as Language: Large Language Models for Scalable Stellar Parameter and Abundance Inference
by: Lu, Hai-Ling, et al.
Published: (2026)