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Abstract: We present FLINT (learning-based FLow estimation and temporal INTerpolation), a novel deep learning-based approach to estimate flow fields for 2D+time and 3D+time scientific ensemble data.

Abstract: The success of deep learning heavily relies on the large amount of training samples. However, in scientific visualization, due to the high computational cost, only few data are available ...