Adjoint-aided inference of Gaussian process driven differential equations
(2022)
Conference Proceeding
Gahungu, P., Lanyon, C. W., Álvarez, M. A., Smith, M. T., & Wilkinson, R. D. (2022). Adjoint-aided inference of Gaussian process driven differential equations. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems 35 (NeurIPS 2022)
Linear systems occur throughout engineering and the sciences, most notably as differential equations. In many cases the forcing function for the system is unknown, and interest lies in using noisy observations of the system to infer the forcing, as w... Read More about Adjoint-aided inference of Gaussian process driven differential equations.