Advancing Cosmological Parameter Estimation and Hubble Parameter Reconstruction with Long Short-term Memory and Efficient Kolmogorov–Arnold Networks

Advancing Cosmological Parameter Estimation and Hubble Parameter Reconstruction with Long Short-term Memory and Efficient Kolmogorov–Arnold Networks

In this work, we propose a novel approach for cosmological parameter estimation and Hubble parameter reconstruction using long short-term memory (LSTM) networks and efficient Kolmogorov–Arnold networks (Ef-KAN). LSTM networks are employed to extract features from observational data, enabling accurat...

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Bibliographic Details
Main Authors: Jiaxing Cui, Marek Biesiada, Ao Liu, Cuihong Wen, Tonghua Liu, Jieci Wang
Format: Article
Language:English
Published: IOP Publishing 2025-01-01
Series:The Astrophysical Journal Supplement Series
Subjects:
Cosmological parameters from large-scale structure
Maximum likelihood estimation
Bayesian statistics
Astrostatistics
Online Access:https://doi.org/10.3847/1538-4365/adef3f
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https://doi.org/10.3847/1538-4365/adef3f

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