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07/21/2023
Data-Induced Interactions of Sparse Sensors
Large-dimensional empirical data in science and engineering frequently h...
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06/23/2023
Optimal Sensor Placement with Adaptive Constraints for Nuclear Digital Twins
Given harsh operating conditions and physical constraints in reactors, n...
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08/24/2020
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
Data science, and machine learning in particular, is rapidly transformin...
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05/13/2020
Kernel Analog Forecasting: Multiscale Test Problems
Data-driven prediction is becoming increasingly widespread as the volume...
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04/01/2018
Sparse Principal Component Analysis via Variable Projection
Sparse principal component analysis (SPCA) has emerged as a powerful tec...
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11/24/2017
Predicting shim gaps in aircraft assembly with machine learning and sparse sensing
A modern aircraft may require on the order of thousands of custom shims ...
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03/27/2017
Randomized CP Tensor Decomposition
The CANDECOMP/PARAFAC (CP) tensor decomposition is a popular dimensional...
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01/12/2017