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Equivariant flow-based sampling for lattice gauge theory., , , , , , , and . CoRR, (2020)Adversarial Variational Optimization of Non-Differentiable Simulators., , and . BNAIC/BENELEARN, volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)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.Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions., , , , , , , , , and 2 other author(s). CoRR, (2022)The frontier of simulation-based inference, , and . (2019)Machine learning and the physical sciences, , , , , , , and . (2019)cite arxiv:1903.10563.Unifying generative models and exact likelihood-free inference with conditional bijections, and . (2016)Discovering Symbolic Models from Deep Learning with Inductive Biases., , , , , , and . NeurIPS, (2020)Etalumis: bringing probabilistic programming to scientific simulators at scale., , , , , , , , , and 7 other author(s). SC, page 29:1-29:24. ACM, (2019)Normalizing Flows on Tori and Spheres., , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 8083-8092. PMLR, (2020)