Numerical Approximations of Log Gaussian Cox Process (Student Abstract)

Authors

  • Francois Buet-Golfouse University College London
  • Hans Roggeman Independent

DOI:

https://doi.org/10.1609/aaai.v36i11.21598

Keywords:

Log Gaussian Cox Process, Laplace Method, Compartmental Model, Numerical Approximation

Abstract

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.
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Published

2022-06-28

How to Cite

Buet-Golfouse, F., & Roggeman, H. (2022). Numerical Approximations of Log Gaussian Cox Process (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12923-12924. https://doi.org/10.1609/aaai.v36i11.21598

Issue

Vol. 36 No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program