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Learning temporal coherence via self-supervision for GAN-based video generation., , , , and . ACM Trans. Graph., 39 (4): 75 (2020)Learning meaningful controls for fluids., , , , and . ACM Trans. Graph., 40 (4): 100:1-100:13 (2021)Data-driven synthesis of smoke flows with CNN-based feature descriptors., and . ACM Trans. Graph., 36 (4): 69:1-69:14 (2017)tempoGAN: a temporally coherent, volumetric GAN for super-resolution fluid flow., , , and . ACM Trans. Graph., 37 (4): 95 (2018)Temporally Coherent GANs for Video Super-Resolution (TecoGAN)., , , and . CoRR, (2018)Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution., , , and . CoRR, (2019)Physics informed neural fields for smoke reconstruction with sparse data., , , , , , and . ACM Trans. Graph., 41 (4): 119:1-119:14 (2022)Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution., , , and . IEEE Trans. Vis. Comput. Graph., 27 (6): 3064-3078 (2021)Detail Synthesis for Fluids and Videos with Deep-Learning Algorithms.. Technical University of Munich, Germany, (2020)A Multi-Pass GAN for Fluid Flow Super-Resolution., , , and . Proc. ACM Comput. Graph. Interact. Tech., 2 (2): 10:1-10:21 (2019)