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Uncertainty-Aware Model-Constrained Neural Digital Twins for Real-Time Forecast, Calibration, and Control of Aeroelastic Airfoils
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Rendezvous Planning from Sparse Observations of Optimally Controlled Targets
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Model-constrained uncertainty quantification for scientific deep learning of inverse solutions
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Solving Bayesian Inverse Problems via Variational Autoencoders
In recent years, the field of machine learning has made phenomenal progress in the pursuit of simulating real-world data generation …
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