Resultados de búsqueda - Qiang, Li-e

Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows por Liang, Bo, Du, Minghui, Wang, He, Xu, Yuxiang, Liu, Chang, Wei, Xiaotong, Xu, Peng, Qiang, Li-e, Luo, Ziren

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Accelerating Stochastic Gravitational Wave Backgrounds Parameter Estimation in Pulsar Timing Arrays with Flow Matching por Liang, Bo, Liu, Chang, Zhao, Tianyu, Du, Minghui, Liang, Manjia, Shi, Ruijun, Guo, Hong, Xu, Yuxiang, Qiang, Li-e, Xu, Peng, Qian, Wei-Liang, Luo, Ziren

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Estimating Orbital Parameters of Direct Imaging Exoplanet Using Neural Network por Liang, Bo, Song, Hanlin, Liu, Chang, Zhao, Tianyu, Xu, Yuxiang, Xiao, Zihao, Liang, Manjia, Du, Minghui, Qian, Wei-Liang, Qiang, Li-e, Xu, Peng, Luo, Ziren

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FluxMC: Rapid and High-Fidelity Inference for Space-Based Gravitational-Wave Observations por Liang, Bo, Liu, Chang, Song, Hanlin, Zhao, Tianyu, Du, Minghui, Wang, He, Gu, Haohao, He, Sensen, Xu, Yuxiang, Qian, Wei-Liang, Qiang, Li-e, Xu, Peng, Luo, Ziren, Sun, Mingming

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High-Precision Ground Characterization of Test-Mass Magnetic Properties for the Taiji Gravitational Wave Mission via a Physics-Informed Neural Framework por Liu, Chang, Deng, Qiong, Li, Huadong, Yang, Liwei, Peng, Xiaodong, Luo, Ziren, Zhang, Yuzhu, Gao, Chen, Wei, Xiaotong, Du, Minghui, Xiao, Zihao, Xu, Peng, Liang, Bo, Wang, Zhi, Qiang, Li-e

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Unlocking New Paths for Science with Extreme-Mass-Ratio Inspirals: Machine Learning-Enhanced MCMC for Accurate Parameter Inversion por Liang, Bo, Liu, Chang, Song, Hanlin, Lyu, Zhenwei, Du, Minghui, Xu, Peng, Luo, Ziren, He, Sensen, Gu, Haohao, Zhao, Tianyu, Xu, Manjia Liang Yuxiang, Qiang, Li-e, Sun, Mingming, Qian, Wei-Liang

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