Physics-informed constraints on implicit neural representations yield more accurate and stable predictions of stirred-tank flows than purely data-driven models when training data is scarce, with diminishing returns at larger dataset sizes.
Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=
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Accelerated and data-efficient flow prediction in stirred tanks via physics-informed learning
Physics-informed constraints on implicit neural representations yield more accurate and stable predictions of stirred-tank flows than purely data-driven models when training data is scarce, with diminishing returns at larger dataset sizes.