In this Letter, we demonstrate that applying deep generative machine learning models for
lattice field theory is a promising route for solving problems where Markov chain Monte …

We show how to use the path-wise derivative estimator for both the forward reverse Kullback–
Leibler divergence for any practically invertible normalizing flow. The resulting path-gradient …

Estimating the free energy, as well as other thermodynamic observables, is a key task in
lattice field theories. Recently, it has been pointed out that deep generative models can be …

Accompanied by the fast evolution of graphical processing units, there is a rapid
development of deep learning methods with applications in almost all natural and applied …