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FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks
Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems.
AutoCT: Automated CT registration, segmentation, and quantification
The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications.
Non-intrusive Nonlinear Model Reduction via Machine Learning Approximations to Low-dimensional Operators
Although projection-based reduced-order models (ROMs) for parameterized nonlinear dynamical systems have demonstrated exciting results across a range of applications, their broad adoption has been limited by their intrusivity: implementing such a reduced-order model typically requires significant modifications to the underlying simulation code.
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