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Photometric Redshift Estimation
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Determination of galaxy photometric redshifts using Conditional Generative Adversarial Networks (CGANs)
Using different sources of ground truths and transfer learning to improve the generalization of photometric redshift estimation
CLAP. I. Resolving miscalibration for deep learning-based galaxy photometric redshift estimation
Preliminary Report on Mantis Shrimp: a Multi-Survey Computer Vision Photometric Redshift Model
AstroCLIP: A Cross-Modal Foundation Model for Galaxies
Towards Instance-Wise Calibration: Local Amortized Diagnostics and Reshaping of Conditional Densities (LADaR)
Photometric Redshift Estimation with Convolutional Neural Networks and Galaxy Images: A Case Study of Resolving Biases in Data-Driven Methods
Scalable Statistical Inference of Photometric Redshift via Data Subsampling
Self-Supervised Representation Learning for Astronomical Images
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference
A Sparse Gaussian Process Framework for Photometric Redshift Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.