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sir models
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Comparing Manifold-Constrained Gaussian Processes and Physics-Inspired Neural Networks for Parameter Inference in Epidemiological Models
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Year
Spring 2025
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School
Emory College
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Department / Specialty
Mathematics
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Degree
B.S.
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Submission Type
Honors Thesis
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Applied Mathematics
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Statistics
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Alessandro Veneziani, Emory University
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David Hirshberg, Emory University
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Yuanzhe Xi, Emory University
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gaussian processes
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machine learning
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parameter inference
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physics-inspired neural networks
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sir models
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