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Flow-based generative models for Markov chain Monte Carlo in lattice field theory., , and . CoRR, (2019)Flow-based sampling for fermionic lattice field theories., , , , , , , , and . CoRR, (2021)Neural-network preconditioners for solving the Dirac equation in lattice gauge theory., , , , and . CoRR, (2022)Introduction to Normalizing Flows for Lattice Field Theory, , , , , , , and . (2021)cite arxiv:2101.08176Comment: 38 pages, 5 numbered figures, Jupyter notebook included as ancillary file.Equivariant flow-based sampling for lattice gauge theory., , , , , , , and . CoRR, (2020)Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions., , , , , , , , , and 2 other author(s). CoRR, (2022)Practical applications of machine-learned flows on gauge fields., , , , , , , and . CoRR, (2024)Normalizing Flows on Tori and Spheres., , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 8083-8092. PMLR, (2020)