| Abstract: |
| We approach the data-driven learning problem for a general second order ODE agent-based system with multiple species. By modeling with interaction kernels, we can use a Gaussian Process approach to learn a nonparametric model for the dynamical system with built-in uncertainty quantification. In this talk, we develop the modeling system, present theoretical analysis on the learning methodology, and present empirical investigations into scalability and practicality using a biological predator-prey model. |
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