Abstract
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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