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arxiv:2202.08177
Generative modeling with projected entangled-pair states
Published on Feb 16, 2022
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Abstract
Projected entangled-pair states (PEPS) outperform matrix product states for generating two-dimensional datasets like images using an efficient sampling algorithm.
AI-generated summary
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.
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