GalaxiesML: a dataset of galaxy images, photometry, redshifts, and structural parameters for machine learning

Documenti analoghi

• Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models
  di: Li, Yun Qi, et al.
  Pubblicazione: (2024)
• Improving Generalization and Uncertainty Quantification of Photometric Redshift Models
  di: Soriano, Jonathan, et al.
  Pubblicazione: (2026)
• Combining datasets with different ground truths using Low-Rank Adaptation to generalize image-based CNN models for photometric redshift prediction
  di: Seenivasan, Vikram, et al.
  Pubblicazione: (2026)
• Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation
  di: Soriano, Jonathan, et al.
  Pubblicazione: (2024)
• Improving Photometric Redshift Estimation for Cosmology with LSST using Bayesian Neural Networks
  di: Jones, Evan, et al.
  Pubblicazione: (2023)