Generative modeling with projected entangled-pair states
Tom Vieijra, Laurens Vanderstraeten, Frank Verstraete · arXiv (Cornell University) · 2022
We argue and demonstrate that projected entangled-pair states (PEPS) outperform matrix product states significantly for the task of generative modeling of datasets with an intrinsic two-dimensional structure such as images. Our approach builds on a recently introduced algorithm for sampling PEPS, which allows for the efficient optimization and sampling of the distributions.