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Marie-Lena Eckert, Kiwon Um, Nils Thuerey
2019 ACM Transactions on Graphics  
In this paper, we present ScalarFlow, a first large-scale data set of reconstructions of real-world smoke plumes.  ...  Our data set includes a large number of complex and natural buoyancy-driven flows. The flows transition to turbulent flows and contain observable scalar transport processes.  ...  Thus, our setup is representative for the ScalarFlow: A Large-Scale Volumetric Data Set of Real-world Scalar Transport Flows for Computer Animation and Machine Learning • 239:3 commonly used hot smoke  ... 
doi:10.1145/3355089.3356545 fatcat:62d4nkf3ebhavndinjpemmj3zm

Learning Similarity Metrics for Numerical Simulations [article]

Georg Kohl, Kiwon Um, Nils Thuerey
2020 arXiv   pre-print
Additionally, we analyze generalization benefits of an adjustable training data difficulty and demonstrate the robustness of LSiM via an evaluation on three real-world data sets.  ...  To demonstrate that the proposed approach outperforms existing metrics for vector spaces and other learned, image-based metrics, we evaluate the different methods on a large range of test data.  ...  We would like to thank Stephan Rasp for preparing the WeatherBench data and all reviewers for helping to improve this work.  ... 
arXiv:2002.07863v2 fatcat:chi2mlzmqjc2bjczbw3e7nyfae