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1
Overcoming Small Datasets in Machine Learning Studies of Multi-Physics Flows in Propulsion.
Overcoming Small Datasets in Machine Learning Studies of Multi-Physics Flows in Propulsion.
Chung, Wai Tong. | Stanford University. | 2024
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2
Dimensional Reduction of Adaptively Refined Nonlinear Computational Models.
Dimensional Reduction of Adaptively Refined Nonlinear Computational Models.
Little, Clayton. | Stanford University. | 2024
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3
Model-Driven Discovery Through a Whole-Cell Computational Model of Escherichia Coli.
Model-Driven Discovery Through a Whole-Cell Computational Model of Escherichia Coli.
Sun, Gwanggyu. | Stanford University. | 2024
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4
Mean Field Methods for Stochastic Control and Optimization Problems.
Mean Field Methods for Stochastic Control and Optimization Problems.
Hui, Yue. | Stanford University. | 2021
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5
Neural Network Verification for Nonlinear Systems.
Neural Network Verification for Nonlinear Systems.
Sidrane, Chelsea Rose. | Stanford University. | 2022
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6
Application of Macroscopic Forcing Method (MFM) for Revealing Turbulence Closure Model Requirements.
Application of Macroscopic Forcing Method (MFM) for Revealing Turbulence Closure Model Requirements.
Shirian, Yasaman. | Stanford University. | 2022
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7
Mathematical Models of Rhythm Synchronization and Anticipation.
Mathematical Models of Rhythm Synchronization and Anticipation.
Roman Guzman, Iran Rafael. | Stanford University. | 2021
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