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Uncovering wall-shear stress dynamics from neural-network enhanced fluid flow measurements
Friction drag from a turbulent fluid moving past or inside an object plays a crucial role in domains as diverse as transportation, public utility infrastructure, energy technology, and human health.
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers
We focus on the setting in which data are available from multiple different instances of a system whose underlying dynamical model is entirely unknown at the outset.
Deep Learning of Causal Structures in High Dimensions
Recent years have seen rapid progress at the intersection between causality and machine learning.
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