HMCF - Hamiltonian Monte Carlo Sampling for Fields -一个使用NIFTy进行HMC采样的Python框架
HMCF - Hamiltonian Monte Carlo Sampling for Fields - A Python framework for HMC sampling with NIFTy
摘要：
HMCF“Hamiltonian Monte Carlo for Fields”是NIFTy“数值信息场论“框架的一个软件插件，在Python中实现了Hamiltonian Monte Carlo（HMC）采样。HMCF和NIFTy旨在解决高维空间相关设置（如图像重建）中的推理问题。HMCF为NIFTY增加了一个HMC采样器，可以自动调整许多自由参数，控制HMC采样机器。各种各样的功能，确保高效的全后验抽样高维推理问题。这些功能包括集成步长调整，评估的质量矩阵，收敛诊断，高阶辛积分和贝叶斯分层模型中的参数和超参数的同时采样。
英文摘要：
HMCF "Hamiltonian Monte Carlo for Fields" is a software add-on for the NIFTy "Numerical Information Field Theory" framework implementing Hamiltonian Monte Carlo (HMC) sampling in Python. HMCF as well as NIFTy are designed to address inference problems in high-dimensional spatially correlated setups such as image reconstruction. HMCF adds an HMC sampler to NIFTy that automatically adjusts the many free parameters steering the HMC sampling machinery. A wide variety of features ensure efficient full-posterior sampling for high-dimensional inference problems. These features include integration step size adjustment, evaluation of the mass matrix, convergence diagnostics, higher order symplectic integration and simultaneous sampling of parameters and hyperparameters in Bayesian hierarchical models.
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