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Gauge-equivariant flow models for sampling in lattice field theories with pseudofermions., , , , , , , , , and 2 other author(s). CoRR, (2022)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.Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382)., , , , and . Dagstuhl Reports, 12 (9): 150-199 (September 2022)Discovering Symbolic Models from Deep Learning with Inductive Biases, , , , , , and . Advances in Neural Information Processing Systems, 33, page 17429--17442. Curran Associates, Inc., (2020)pyhf: pure-Python implementation of HistFactory statistical models., , , and . J. Open Source Softw., 6 (58): 2823 (2021)Set2Graph: Learning Graphs From Sets., , , , , , and . NeurIPS, (2020)PhysicsGP: A Genetic Programming Approach to Event Selection, and . (February 2004)Comment: 16 pages 9 figures, 1 table. Submitted to Comput. Phys. Commun.Mining gold from implicit models to improve likelihood-free inference, , , and . (2018)cite arxiv:1805.12244Comment: Code available at https://github.com/johannbrehmer/simulator-mining-example . v2: Fixed typos. v3: Expanded discussion, added Lotka-Volterra example. v4: Improved clarity.