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20232026
most citedEstimating Photometric Redshift from Mock Flux for CSST Survey by using Weighted Random Forest

1 citations · 1 across the 11 of their papers we have counts for

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astro-ph.GA2026

Joint constraints on gravity and stellar orbital anisotropy in massive galaxies

Wei Du, Liping Fu, Gong-Bo Zhao +5

Strong gravitational lensing combined with stellar dynamics provides a complementary route for testing gravity on kiloparsec scales and probing the internal structure of massive ga…

astro-ph.GA2026

Comparative analysis of missing data imputation methods for CSST survey: Impact on photometric redshift estimation performance

Ling Wang, Zhu Chen, Zhijian Luo +42

Improving the accuracy of photometric redshifts (photo-) is essential for reliable statistical studies of cosmology and galaxy evolution. However, missing photometric bands are…

astro-ph.GA2025

LSTM-MDNz: Estimating Quasar Photometric Redshifts with an LSTM-Augmented Mixture Density Network

Jianzhen Chen, Zhijian Luo, Liping Fu +4

Quasar photometric redshifts are essential for studying cosmology and large-scale structures. However, their complex spectral energy distributions cause significant redshift-color…

astro-ph.GA2025

Galaxy Morphology Classification via Deep Semi-Supervised Learning with Limited Labeled Data

Zhijian Luo, Jianzhen Chen, Zhu Chen +4

Galaxy morphology classification plays a crucial role in understanding the structure and evolution of the universe. With galaxy observation data growing exponentially, machine lear…

astro-ph.GA2024

Photometric Redshift Estimation for CSST Survey with LSTM Neural Networks

Zhijian Luo, Yicheng Li, Junhao Lu +11

Accurate estimation of photometric redshifts (photo-s) is crucial for cosmological surveys. Various methods have been developed for this purpose, such as template fitting method…