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Flow-based generative models for Markov chain Monte Carlo in lattice field theory., , and . CoRR, (2019)Flow-based sampling in the lattice Schwinger model at criticality., , , , , , , , , and . CoRR, (2022)Neural-network preconditioners for solving the Dirac equation in lattice gauge theory., , , , and . CoRR, (2022)Flow-based sampling for fermionic lattice field theories., , , , , , , , and . CoRR, (2021)Normalizing Flows on Tori and Spheres., , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 8083-8092. PMLR, (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)Equivariant flow-based sampling for lattice gauge theory., , , , , , , and . CoRR, (2020)Flow-based sampling for multimodal distributions in lattice field theory., , , , , , , , and . CoRR, (2021)Introduction to Normalizing Flows for Lattice Field Theory., , , , , , , and . CoRR, (2021)