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Spectral Reconstruction with Deep Neural Networks., , , , , , , and . CoRR, (2019)Flow-based sampling for fermionic lattice field theories., , , , , , , , and . CoRR, (2021)Aspects of scaling and scalability for flow-based sampling of lattice QCD., , , , , , , , , and 3 other author(s). CoRR, (2022)Normalizing flows for lattice gauge theory in arbitrary space-time dimension., , , , , , , , , and 4 other author(s). CoRR, (2023)Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions., , , , , , , , , and 2 other author(s). CoRR, (2022)Flow-based density of states for complex actions., and . CoRR, (2022)Flow-based sampling in the lattice Schwinger model at criticality., , , , , , , , , and . CoRR, (2022)Reducing autocorrelation times in lattice simulations with generative adversarial networks., and . Mach. Learn. Sci. Technol., 1 (4): 45011 (2020)Applications of flow models to the generation of correlated lattice QCD ensembles., , , , , , , , , and . CoRR, (2024)Towards Novel Insights in Lattice Field Theory with Explainable Machine Learning., , , , and . CoRR, (2020)