标题： 利用贝叶斯神经网络从N体模拟中限制宇宙学参数 显示英文标题

标题： Constraining cosmological parameters from N-body simulations with Bayesian Neural Networks

摘要： 本文中，我们利用 Quijote 模拟来通过贝叶斯神经网络提取宇宙学参数。 这类模型具有估算相关不确定性的显著能力，这是精确宇宙学时代的目标之一。 我们展示了贝叶斯神经网络从模拟中提取更复杂的输出分布和非高斯信息的优势。 显示英文摘要

摘要： In this paper, we use The Quijote simulations in order to extract the cosmological parameters through Bayesian Neural Networks. This kind of model has a remarkable ability to estimate the associated uncertainty, which is one of the ultimate goals in the precision cosmology era. We demonstrate the advantages of BNNs for extracting more complex output distributions and non-Gaussianities information from the simulations.