Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification
Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, they can be effectively processed to extract astronomical patterns and information. In this study, we present a comprehensive evaluation of models bas...
Saved in:
| Main Authors: | Yu-Yang Li, Yu Bai, Cunshi Wang, Mengwei Qu, Ziteng Lu, Roberto Soria, Jifeng Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2025-01-01
|
| Series: | Intelligent Computing |
| Online Access: | https://spj.science.org/doi/10.34133/icomputing.0110 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Simulating a Stellar Binary Merger. II. Obtaining a Light Curve
by: Roger W. M. Hatfull, et al.
Published: (2025-01-01) -
Polka-dotted Stars: A Hierarchical Model for Mapping Stellar Surfaces Using Occultation Light Curves and the Case of TOI-3884
by: Sabina Sagynbayeva, et al.
Published: (2025-01-01) -
Classification of Exoplanetary Light Curves Using Artificial Intelligence
by: Leticia Flores-Pulido, et al.
Published: (2025-05-01) -
Measuring Long Stellar Rotation Periods (>10 days) from TESS FFI Light Curves is Possible: An Investigation Using TESS and ZTF
by: Soichiro Hattori, et al.
Published: (2025-01-01) -
Galaxy morphology classification: are stellar circularities enough?
by: Baucalo Katarina, et al.
Published: (2025-01-01)