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1
Application-Driven Design of Machine Learning Surrogate Models in Catalysis
Application-Driven Design of Machine Learning Surrogate Models in Catalysis
Sunshine, Ethan M. | Carnegie Mellon University | 2025
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2
Modeling of Electromagnetic Responses With Respect to Design Variables: Local Gradients, Surrogate Modeling, and Deep Learning Neural Network
Modeling of Electromagnetic Responses With Respect to Design Variables: Local Gradients, Surrogate Modeling, and Deep Learning Neural Network
Zhang, Botian. | University of California, Los Angeles | 2024
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3
Development and Assessment of Machine Learning Techniques for Non-Intrusive Probabilistic Surrogate Modeling of High-Fidelity Nuclear Reactor Simulations
Development and Assessment of Machine Learning Techniques for Non-Intrusive Probabilistic Surrogate Modeling of High-Fidelity Nuclear Reactor Simulations
LaFleur, Brandon. | University of Michigan | 2024
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4
Data-Driven Digital Twins for Health-Aware Supervisory Control of Nuclear Reactors
Data-Driven Digital Twins for Health-Aware Supervisory Control of Nuclear Reactors
Lim, Jasmin Y. | University of Michigan | 2025
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5
Numerical Simulations and Machine Learning Surrogates for Predicting Solidification Microstructure in Additive Manufacturing
Numerical Simulations and Machine Learning Surrogates for Predicting Solidification Microstructure in Additive Manufacturing
Qin, Yigong | The University of Texas at Austin | 2025
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6
Data-Driven Geometric Field Prediction Methods and Engineering Applications
Data-Driven Geometric Field Prediction Methods and Engineering Applications
Ferguson, Kevin M. | Carnegie Mellon University | 2025
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