/poisson_process_inference

Simple implementation of Tractable and Scalable nonparametric Bayesian inference in NHPP

Primary LanguagePython

poisson_process_inference

Replicated algorithms proposed by Samo and Roberts (2014) and Adams et al. (2009b)

[1] R. P. Adams, I. Murray, and D. J. C. MacKay, “Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities,” in Proceedings of the 26th Annual International Conference on Machine Learning, ser. ICML ’09. New York, NY, USA: ACM, 2009, pp. 9–16. http://doi.acm.org/10.1145/1553374.1553376

[2] Y.-L. Kom Samo and S. Roberts, “Scalable Nonparametric Bayesian Inference on Point Processes with Gaussian Processes,” ArXiv e-prints, Oct. 2014. http://proceedings.mlr.press/v37/samo15.pdf

[3] I. Murray, R. Prescott Adams, and D. J. C. MacKay, “Elliptical slice sampling,” ArXiv e-prints, Dec. 2010. https://arxiv.org/abs/1001.0175