Numerical Approximations of Log Gaussian Cox Process (Student Abstract)

No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 36

AAAI Student Abstract and Poster Program

This paper considers a multi-state Log Gaussian Cox Process (`"LGCP'') on a graph, where transmissions amongst states are calibrated using a non-parametric approach. We thus consider multi-output LGCPs and introduce numerical approximations to compute posterior distributions extremely quickly and in a completely transparent and reproducible fashion. The model is tested on historical data and shows very good performance.

10.1609/aaai.v36i11.21598